@mastersthesis {2438,
	title = {Advancement of Defect Detection and Quantifying Measurement Uncertainty in X-Ray CT Inspection},
	volume = {PhD in Sciences: Physics},
	year = {2026},
	type = {PhD thesis},
	author = {Miroslav Yosifov}
}
@mastersthesis {2433,
	title = {Advances in Monte Carlo simulations for the design of X-ray phase contrast imaging systems},
	volume = {PhD in Science: Physics},
	year = {2026},
	type = {PhD thesis},
	author = {Jonathan Sanctorum}
}
@article {2436,
	title = {Combining magnetic resonance imaging and evoked potentials enhances machine learning prediction of multiple sclerosis disability worsening},
	journal = {Frontiers in Immunology},
	volume = {17},
	year = {2026},
	doi = {https://doi.org/10.3389/fimmu.2026.1625837},
	author = {Sofie Aerts and Lorin Werthen-Brabants and Hamza Khan and Diana Giraldo and Edward De Brouwer and Lotte Geys and Veronica Popescu and Jan Sijbers and Henry C. Woodruff and Tom Dhaene and Dirk Deschrijver and Bart Van Wijmeersch and Philippe Lambin and Liesbet M. Peeters}
}
@inproceedings {2442,
	title = {Cycloidal Acquisition for Inline Edge Illumination X-ray Phase Contrast Computed Tomography: A Simulation Study},
	booktitle = {15th Conference on Industrial Computed Tomography (iCT)},
	volume = {31},
	year = {2026},
	month = {February},
	address = {Linz, Austria},
	keywords = {computed tomography, edge illumination, inline acquisition, X-ray phase contrast imaging},
	doi = {10.58286/32604},
	url = {https://doi.org/10.58286/32604},
	author = {Verstraete, J. and Francken, N. and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2437,
	title = {Edge illumination phase contrast imaging  with continuous motion},
	volume = {PhD in Sciences: Physics},
	year = {2026},
	month = {February, 2026},
	type = {PhD thesis},
	author = {Ben Huyge}
}
@article {2423,
	title = {Framework for optimal design of a multi-source rectangular X-ray cargo scanning system},
	journal = {Radiation Physics and Chemistry},
	volume = {239},
	year = {2026},
	pages = {113332},
	doi = {https://doi.org/10.1016/j.radphyschem.2025.113332 },
	author = {Caroline Bossuyt and Arnold Jan den Dekker and Domenico Iuso and Jan De Beenhouwer and Jan Sijbers}
}
@article {2428,
	title = {From Skin to Skeleton: A Statistical Shape Modelling Approach for Predicting Hand and Foot Bony Geometry},
	journal = {Annals of Biomedical Engineering},
	volume = {54},
	year = {2026},
	pages = {284-302},
	doi = {https://doi.org/10.1007/s10439-025-03882-0},
	author = {Kate Duquesne and Molnar Adris and Roel Huysentruyt and Aline Van Oevelen and Jing Li and Jan Sijbers and Wim Van Paepegem and Emmanuel Audenaert}
}
@inproceedings {2447,
	title = {GEO-ASTRA: a toolbox for non-conventional XCT scanning and reconstruction},
	booktitle = { 15th Conference on Industrial Computed Tomography (iCT), 10 - 13 February 2026, Linz, Austria (iCT 2026), e-Journal of Nondestructive Testing},
	volume = {31 (3)},
	year = {2026},
	doi = {https://doi.org/10.58286/32567},
	author = {Joaquim G. Sanctorum and Bjorn De Samber and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2443,
	title = {Inline Edge Illumination Computed Tomography: A Simulation Study},
	booktitle = {2026 IEEE 23rd Mediterranean Electrotechnical Conference (MELECON)},
	year = {2026},
	address = {Cairo, Egypt},
	keywords = {edge illumination, Industry 4.0, Inline inspection, Non-destructive testing, X-ray phase contrast computed tomography},
	doi = {https://doi.org/10.1109/MELECON64486.2026.11418832},
	author = {Verstraete, J. and Francken, N. and Jan Sijbers and Jan De Beenhouwer}
}
@article {2432,
	title = {Investigating the Influence of Individual Physical Effects on Dimensional Measurement Deviations Using XCT Simulations},
	journal = {Measurement,},
	volume = {263},
	year = {2026},
	doi = {https://doi.org/10.1016/j.measurement.2025.120168},
	author = {Miroslav Yosifov and Thiago Linhares Fernandes and Filippo Zanini and Simone Carmignato and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2448,
	title = {Towards X-ray-based inspection of corrosion in maritime infrastructure},
	booktitle = {15th Conference on Industrial Computed Tomography (iCT), 10 - 13 February 2026, Linz, Austria (iCT 2026) Special Issue of e-Journal of Nondestructive Testing (eJNDT) ISSN 1435-4934 },
	volume = {31(3)},
	year = {2026},
	doi = {https://doi.org/10.58286/32583},
	author = {Joaquim G. Sanctorum and Nathan Bekaert and Wikke Witteveen and Geert Potters and Jan Sijbers and Jan De Beenhouwer}
}
@article {2457,
	title = {Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3{\textemdash}Ex vivo imaging: Data processing, comparisons with microscopy, and tractography},
	journal = {Magnetic Resonance in Medicine},
	volume = {93},
	year = {2025},
	month = {Jan-06-2025},
	pages = {2561 - 2582},
	issn = {0740-3194},
	doi = {10.1002/mrm.v93.610.1002/mrm.30424},
	url = {https://onlinelibrary.wiley.com/toc/15222594/93/6https://onlinelibrary.wiley.com/doi/10.1002/mrm.30424https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.30424},
	author = {Schilling, Kurt G. and Howard, Amy F. D. and Grussu, Francesco and Ianus, Andrada and Hansen, Brian and Barrett, Rachel L. C. and Aggarwal, Manisha and Michielse, Stijn and Nasrallah, Fatima and Syeda, Warda and Wang, Nian and Veraart, Jelle and Roebroeck, Alard and Bagdasarian, Andrew F. and Eichner, Cornelius and Sepehrband, Farshid and Zimmermann, Jan and Soustelle, Lucas and Bowman, Christien and Tendler, Benjamin C. and Hertanu, Andreea and Ben Jeurissen and Verhoye, Marleen and Frydman, Lucio and van de Looij, Yohan and Hike, David and Dunn, Jeff F. and Miller, Karla and Landman, Bennett A. and Shemesh, Noam and Anderson, Adam and McKinnon, Emilie and Farquharson, Shawna and Dell{\textquoteright}Acqua, Flavio and Pierpaoli, Carlo and Drobnjak, Ivana and Leemans, Alexander and Harkins, Kevin D. and Descoteaux, Maxime and Xu, Duan and Huang, Hao and Santin, Mathieu D. and Grant, Samuel C. and Obenaus, Andre and Kim, Gene S. and Wu, Dan and Le Bihan, Denis and Blackband, Stephen J. and Ciobanu, Luisa and Els Fieremans and Bai, Ruiliang and Leergaard, Trygve B. and Zhang, Jiangyang and Dyrby, Tim B. and Johnson, G. Allan and Cohen-Adad, Julien and Budde, Matthew D. and Jelescu, Ileana O.}
}
@article {2456,
	title = {Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2{\textemdash}Ex vivo imaging: Added value and acquisition},
	journal = {Magnetic Resonance in Medicine},
	volume = {93},
	year = {2025},
	month = {Jan-06-2025},
	pages = {2535 - 2560},
	issn = {0740-3194},
	doi = {10.1002/mrm.v93.610.1002/mrm.30435},
	url = {https://onlinelibrary.wiley.com/toc/15222594/93/6https://onlinelibrary.wiley.com/doi/10.1002/mrm.30435https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.30435},
	author = {Schilling, Kurt G. and Grussu, Francesco and Ianus, Andrada and Hansen, Brian and Howard, Amy F. D. and Barrett, Rachel L. C. and Aggarwal, Manisha and Michielse, Stijn and Nasrallah, Fatima and Syeda, Warda and Wang, Nian and Veraart, Jelle and Roebroeck, Alard and Bagdasarian, Andrew F. and Eichner, Cornelius and Sepehrband, Farshid and Zimmermann, Jan and Soustelle, Lucas and Bowman, Christien and Tendler, Benjamin C. and Hertanu, Andreea and Ben Jeurissen and Verhoye, Marleen and Frydman, Lucio and van de Looij, Yohan and Hike, David and Dunn, Jeff F. and Miller, Karla and Landman, Bennett A. and Shemesh, Noam and Anderson, Adam and McKinnon, Emilie and Farquharson, Shawna and Dell{\textquoteright}Acqua, Flavio and Pierpaoli, Carlo and Drobnjak, Ivana and Leemans, Alexander and Harkins, Kevin D. and Descoteaux, Maxime and Xu, Duan and Huang, Hao and Santin, Mathieu D. and Grant, Samuel C. and Obenaus, Andre and Kim, Gene S. and Wu, Dan and Le Bihan, Denis and Blackband, Stephen J. and Ciobanu, Luisa and Els Fieremans and Bai, Ruiliang and Leergaard, Trygve B. and Zhang, Jiangyang and Dyrby, Tim B. and Johnson, G. Allan and Cohen-Adad, Julien and Budde, Matthew D. and Jelescu, Ileana O.}
}
@article {2455,
	title = {Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging},
	journal = {Magnetic Resonance in Medicine},
	volume = {93},
	year = {2025},
	month = {Jan-06-2025},
	pages = {2507 - 2534},
	issn = {0740-3194},
	doi = {10.1002/mrm.v93.610.1002/mrm.30429},
	url = {https://onlinelibrary.wiley.com/toc/15222594/93/6https://onlinelibrary.wiley.com/doi/10.1002/mrm.30429https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.30429},
	author = {Jelescu, Ileana O. and Grussu, Francesco and Ianus, Andrada and Hansen, Brian and Barrett, Rachel L. C. and Aggarwal, Manisha and Michielse, Stijn and Nasrallah, Fatima and Syeda, Warda and Wang, Nian and Veraart, Jelle and Roebroeck, Alard and Bagdasarian, Andrew F. and Eichner, Cornelius and Sepehrband, Farshid and Zimmermann, Jan and Soustelle, Lucas and Bowman, Christien and Tendler, Benjamin C. and Hertanu, Andreea and Ben Jeurissen and Verhoye, Marleen and Frydman, Lucio and van de Looij, Yohan and Hike, David and Dunn, Jeff F. and Miller, Karla and Landman, Bennett A. and Shemesh, Noam and Anderson, Adam and McKinnon, Emilie and Farquharson, Shawna and Dell{\textquoteright}Acqua, Flavio and Pierpaoli, Carlo and Drobnjak, Ivana and Leemans, Alexander and Harkins, Kevin D. and Descoteaux, Maxime and Xu, Duan and Huang, Hao and Santin, Mathieu D. and Grant, Samuel C. and Obenaus, Andre and Kim, Gene S. and Wu, Dan and Le Bihan, Denis and Blackband, Stephen J. and Ciobanu, Luisa and Els Fieremans and Bai, Ruiliang and Leergaard, Trygve B. and Zhang, Jiangyang and Dyrby, Tim B. and Johnson, G. Allan and Cohen-Adad, Julien and Budde, Matthew D. and Schilling, Kurt G.}
}
@inproceedings {2401,
	title = {Correcting for focal spot drift in edge illumination X-ray phase contrast imaging},
	booktitle = {14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium},
	year = {2025},
	doi = {doi.org/10.58286/30746},
	author = {Nicholas Francken and Jonathan Sanctorum and Ben Huyge and Jan Sijbers and Jan De Beenhouwer}
}
@article {2412,
	title = {DAMMER: Direct Adaptive Multi-resolution MEsh Reconstruction from X-ray measurements},
	journal = {IEEE Transactions on Computational Imaging },
	volume = {11},
	year = {2025},
	pages = {926 - 941},
	doi = {10.1109/TCI.2025.3587408},
	author = {Jannes Merckx and Arnold Jan den Dekker and Jan Sijbers and Jan De Beenhouwer}
}
@article {2383,
	title = {Degradation Detection in Rice Products via Shape Variations in XCT Simulation-Empowered AI},
	journal = {Journal of Nondestructive Evaluation},
	volume = {44},
	year = {2025},
	doi = {https://doi.org/10.1007/s10921-024-01147-9},
	author = {Miroslav Yosifov and Thomas Lang and Virginia Florian and Stefan Gerth and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@mastersthesis {2415,
	title = {Edge illumination X-ray phase contrast imaging: Advancements in simulations and inline acquisitions},
	volume = {PhD in Sciences: Physics},
	year = {2025},
	type = {PhD thesis},
	author = {Nicholas Francken}
}
@article {2417,
	title = {Edge illumination X-ray phase contrast imaging with continuous mask motion},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	pages = {41271-41286},
	doi = {https://doi.org/10.1364/OE.570476},
	author = {Ben Huyge and Nicholas Francken and Joaquim Sanctorum and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@article {2385,
	title = {Efficient X-ray dark field contrast simulations using a condensed history approach},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	month = {01/2025},
	pages = {3562-3576},
	doi = {10.1364/OE.544864},
	url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-33-2-3562\&id=567367},
	author = {Nicholas Francken and Jonathan Sanctorum and Ben Huyge and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2452,
	title = {Enhancing AdAPTS: Fast Field Evaporation Simulation with Parametric Local Electrodes for Atom Probe Tomography},
	year = {2025},
	abstract = {Atom probe tomography (APT) is a powerful technique for analyzing the composition of materials at the atomic level. However, no reconstruction method currently fully capitalizes on the spatial resolution potential of APT instrumentation. A model of field evaporation, efficiently and accurately describing ion trajectories, remains essential for reconstruction. To address this, we developed AdAPTS, a simulation tool that improves the efficiency of modeling individual evaporations compared to TAPSim. Both tools, however, lack a local electrode model, which influences ion trajectories. Directly incorporating a local electrode into the finite element mesh hinders simulation speed and memory efficiency. To overcome this, we introduce a local electrode feature in AdAPTS that leverages the superposition principle by projecting a solution of the field emitted by the local electrode onto a mesh of the experimental domain, resulting in constant computational overhead instead of recalculating the total electrostatic field in each iteration. The parametric definition of local electrodes allows for precise modeling of electrode geometries, providing a flexible framework for electrode design and potentially enabling more accurate 3D reconstruction. Future work will focus on integrating additional physical models in AdAPTS to expand its capabilities across diverse material systems.},
	url = {https://ge.iitm.ac.in/apt\&m-2025/schedule.html},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2450,
	title = {Exact reconstruction for helical cone-beam X-ray CT using the ASTRA toolbox},
	booktitle = {10th International Symposium on Digital Industrial Radiology and Computed Tomography, 1 {\textendash} 3 July 2025 in Paris, France (DIR 2025)},
	volume = {30(8)},
	year = {2025},
	url = {https://www.ndt.net/?id=31452},
	author = {Pavel Paramonov and Joaquim G. Sanctorum and Femke Danckaers and Jan De Beenhouwer and Jan Sijbers}
}
@article {2405,
	title = {Gratings for multiresolution edge illumination X-ray phase contrast imaging: concept and simulation},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	pages = {17886-17902},
	doi = {10.1364/OE.550252},
	author = {Pieter-Jan Vanthienen and Nicholas Francken and Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@book {2458,
	title = {Handbook of Diffusion MR Tractography: Multishell models},
	year = {2025},
	pages = {201 - 220},
	publisher = {Elsevier},
	organization = {Elsevier},
	isbn = {9780128188941},
	doi = {10.1016/B978-0-12-818894-1.00008-2},
	author = {Morez, Jan and De Luca, Alberto and Pietsch, Maximillian and Christiaens, Daan and Baete, Steven H. and Reisert, Marco and Ben Jeurissen}
}
@article {2406,
	title = {Harmonization of diffusion MRI on healthy subjects using NeuroCombat and LongCombat: a B-Q MINDED Brain Intra-and Inter-Scanner Study},
	journal = {Frontiers in Neuroscience},
	volume = {19},
	year = {2025},
	doi = {10.3389/fnins.2025.1591169},
	author = {Maira Siqueira Pinto and Vincenzo Anania and Roberto Paolella and Celine Smekens and Thibo Billiet and Thomas Janssens and Arnold Jan den Dekker and Jan Sijbers and Pieter-Jan Guns and Pieter Van Dyck}
}
@inproceedings {2400,
	title = {In-depth imaging of in-vitro tissue models using electrical impedance tomography},
	booktitle = {iCT 2025 - 14th Conference on Industrial Computed Tomography},
	volume = {4 - 7 February},
	year = {2025},
	doi = {doi.org/10.58286/30763},
	author = {Jian Deng and Babu Linkoon P Meenaketan and Saeedeh Ebrahimi Takalloo and Yoke Chin Chai and Tom Torfs and Dries Braeken and Jan De Beenhouwer and Jan Sijbers}
}
@article {2426,
	title = {Leveraging Hand-Crafted Radiomics on Multicenter FLAIR MRI for Predicting Disability Worsening in People with Multiple Sclerosis},
	journal = {Front. Neurosci.},
	volume = {19},
	year = {2025},
	doi = {https://doi.org/10.3389/fnins.2025.1610401},
	author = {Hamza Khan and Diana Giraldo and Henry C. Woodruff and Lorin Werthen-Brabants and Shruti Atul Mali and Sina Amirrajab and Edward De Brouwer and Veronica Popescu and Bart Van Wijmeersch and Oliver Gerlach and Jan Sijbers and Liesbet M. Peeters and Philippe Lambin}
}
@article {2399,
	title = {Loss of the Ubiquitin-Associated Domain of sqstm1/p62 in Zebrafish Causes a Phenotype Resembling Paget{\textquoteright}s Disease of Bone},
	journal = {Calcified Tissue International},
	volume = {116},
	year = {2025},
	pages = {1-15},
	author = {Yentl Huybrechts and Rapha{\"e}l De Ridder and Dylan Bergen and Bjorn De Samber and Eveline Boudin and Francesca Tonelli and Dries Knapen and Lucia Vergauwen and Dorien Schepers and Evelien Van Dijck and Qiao Tong and Anja Verhulst and Jan De Beenhouwer and Jan Sijbers and Chrissy Hammond and Antonella Forlino and Geert Mortier and Paul Coucke and P Eckhard Witten and Ronald Young Kwon and Andy Willaert and Gretl Hendrickx and Wim Van Hul}
}
@article {2434,
	title = {Moisture Content Estimation of Porous Building Stones using Hyperspectral Imaging},
	journal = {Scientific Data},
	volume = {13},
	year = {2025},
	month = {Dec},
	pages = {102},
	abstract = {Moisture poses a major threat to built heritage through processes such as frost damage, salt crystallization and biological growth, which accelerate stone deterioration. Stone moisture content can be determined non-destructively by spectral reflectance in the shortwave infrared (SWIR) wavelength range. To validate this, large cubic and small cylindrical samples from six stone types, Brick, Euville, Massangis, Neubrunn, Obernkirchen, and Savonni{\`e}res, with different controlled moisture levels were prepared, and a comprehensive SWIR hyperspectral image dataset was created. The acquired hyperspectral images were processed using the Normalized Relative Arc Lengths (NRAL) method to generate moisture maps that illustrate the spatial distribution of water within each sample. Because moisture distribution is influenced by pore characteristics and grain arrangement, the moisture maps were validated through petrographic examination. For quantitative validation, the mean moisture content of each sample was compared with the corresponding gravimetric moisture content. The results demonstrated strong agreement between the estimated and gravimetric moisture values, with root mean square errors ranging from 1 and 2 g/g ~{\texttimes} 100.},
	issn = {2052-4463},
	doi = {10.1038/s41597-025-06416-4},
	url = {https://doi.org/10.1038/s41597-025-06416-4},
	author = {Chaghdo, Danish Ali and Koirala, Bikram and Cristina, Laura and De Kock, Tim and Fontaine, Laurent and Hayen, Roald and Paul Scheunders}
}
@article {2388,
	title = {Multi-contrast benchmarking of edge illumination Monte Carlo simulations using virtual gratings},
	journal = {Journal of Applied Physics},
	volume = {137},
	year = {2025},
	pages = {104904},
	doi = {10.1063/5.0244152},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@article {2404,
	title = {A novel Soft Tissue-Integrated Kinematic Solver for skeletal motion: Validation and applications},
	journal = {Computer Methods and Programs in Biomedicine},
	volume = {265},
	year = {2025},
	chapter = {108766},
	doi = {https://doi.org/10.1016/j.cmpb.2025.108766},
	author = {Kate Duquesne and Aline Van Oevelen and Jan Sijbers and Wim Van Paepegem and Emmanuel Audenaert}
}
@article {2407,
	title = {A PHASE-CONTRAST X-RAY IMAGING SYSTEM FOR OBTAINING A DARK-FIELD IMAGE AND A METHOD THEREFOR},
	number = {EP 4 351 425 B1},
	year = {2025},
	author = {Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2392,
	title = {Proximal Neural Networks based reconstruction for few-view CT applications},
	booktitle = {14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium},
	year = {2025},
	author = {H. Le and Caroline Bossuyt and Julie Escoda and Marius Costin and Jan De Beenhouwer and Jan Sijbers}
}
@article {2384,
	title = {Proximity Adjusted Centroid Mapping for Accurate Detection of Nuclei in Dense 3D Cell Systems},
	journal = {Computers in Biology and Medicine},
	volume = {185},
	year = {2025},
	pages = {109561},
	doi = {https://doi.org/10.1016/j.compbiomed.2024.109561},
	author = {Tim Van De Looverbosch and Sarah De Beuckeleer and Frederik De Smet and Jan Sijbers and Winnok De Vos}
}
@mastersthesis {2416,
	title = {Shaping the future: 3D knee morphology analysis and predictive models for data-driven patient selection},
	volume = {PhD in Medicine and Health Sciences},
	year = {2025},
	type = {PhD thesis},
	author = {Jonas Grammens}
}
@article {2425,
	title = {Superimposing Synthetic Defects into Real XCT Data and Segmentation-Based Comparison for Advanced Probability of Detection Evaluation},
	journal = { Journal of Nondestructive Evaluation },
	volume = {44},
	year = {2025},
	doi = {https://doi.org/10.1007/s10921-025-01262-1},
	author = {Miroslav Yosifov and Bernhard Fr{\"o}hler and Jan Sijbers and Jan De Beenhouwer and Johann Kastner and Christoph Heinzl}
}
@mastersthesis {2414,
	title = {Towards adaptive multi-resolution edge illumination X-ray phase contrast imaging},
	volume = {PhD in Sciences: Physics},
	year = {2025},
	type = {PhD thesis},
	author = {Pieter-Jan Vanthienen}
}
@inproceedings {2418,
	title = {About rapid phase-wrapping in terahertz phase contrast imaging},
	booktitle = {SPIE},
	volume = {13141},
	year = {2024},
	pages = {69-73},
	abstract = {Terahertz (THz) imaging has emerged as a powerful technique in diverse fields, ranging from medical diagnostics to material characterization. Due to its lower frequency, compared to x-ray-based techniques, THz imaging provides an alternative view into the internal structures of samples composed of low-density materials. Notably, phase contrast imaging is advantageous as it generally exhibits reduced distortion from refraction and reflection losses compared to attenuation contrast. However, in the course of THz phase measurements, a fresh issue arises. Due to the relatively wide beam shape of THz imaging combined with rapid phase wrapping, a new type of artifact emerges, posing a significant hindrance to the accuracy and reliability of the imaging process. This paper explores the intricate interplay between beam shape dynamics and phase-wrapping mechanisms in THz imaging systems, unraveling the source of the artifacts that arise from this phenomenon.},
	doi = {https://doi.org/10.1117/12.3027665},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410F/About-rapid-phase-wrapping-in-terahertz-phase-contrast-imaging/10.1117/12.3027665.short},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2379,
	title = {AdAPTS: An Adaptive Atom Probe Tomography Simulation Library},
	volume = {30},
	year = {2024},
	doi = {https://doi.org/10.1093/mam/ozae044.017},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2451,
	title = {AdAPTS: An Adaptive Atom Probe Tomography Simulation Library},
	year = {2024},
	abstract = {In atom probe tomography (APT), spatial reconstruction enables volumetric insight into a specimen{\textquoteright}s nanostructure. To this day, a fast reconstruction method which utilizes the true potential of APT in terms of resolution does not exist. A model of its effective inverse, the field evaporation, which provides a physically accurate description of the ion trajectories, is a crucial component in reconstruction. The simulation of each individual evaporation, such as in TAPSim, while being able to model some cases accurately, has been time inefficient. Novel methods track surface meshes, achieving better time efficiency, although at the cost of spatial accuracy.

We introduce AdAPTS, an adaptive atom probe tomography simulation library. AdAPTS is a modular volumetric finite element simulation and specimen modeling library for APT written in C++. It is capable of generating accurate detector hit maps of various specimens, efficiently representing and simulating the experimental domain from specimen to detector. Using AdAPTS, we are able to accurately simulate the field evaporation of various specimens, revealing realistic poles and zone lines.

AdAPTS utilizes a unique high quality mesh generation strategy, in which each individual atom is represented by a vertex carrying material property information (e.g. atomic mass, relative permittivity). To constitute the surrounding vacuum chamber, additional vertices are generated using efficient variable density Poisson disk sampling. The software library TetGen is used to Delaunay-tetrahedralize all generated vertices. This yields a tetrahedral mesh in which each element inherits its material properties from the material property previously assigned to each vertex. The resulting vacuum vertices constitute less than 2\% of the total vertices, effectively allowing for a fast and full-scale simulation without employing the finite element method/boundary element method (FEM/BEM) coupling scheme proposed by Fletcher et al. Simultaneously, this method provides a rigid surface notion that preserves local protrusions due to lattice nanostructure similar to TAPSim by Oberdorfer et al., which in turn preserves zone lines and poles on the hit map.

The modeling of a specimen comprises two steps. In the first step, individual crystal lattices can be defined using Bravais lattice descriptors (e.g. bcc, fcc), the material lattice constant and the Miller indices of the crystallic plane facing the detector. In the second step, the shape of the specimen and dopants contained within are modeled using implicit surfaces and binary set operators (e.g. union, intersection). However, for amorphous materials, the individual atomic positions can also be specified individually or generated by any other means. The height, tip radius and shank angle of an implicit  surface (a truncated cone with a quasi-hemispherical tip) that represents the specimen shape can be specified.

The modular finite element methods library MFEM is utilized to determine the electric field by solving Poisson{\textquoteright}s equation given an electric potential Dirichlet boundary condition at the base of the specimen. Using an Euler-forward scheme with variable time steps, the trajectory starting at each evaporation site is calculated. The trajectory integration is terminated when the trajectory intersects with the detector plane. To conclude, AdAPTS provides an efficient and accurate framework which combines specimen modeling with realistic field evaporation due to voltage pulses using state-of-the-art mesh generation and numerical simulation tools. A thorough quantitative comparison in terms of simulation time of the different simulators will be provided by the time of the conference.},
	url = {https://plan.events.mpg.de/event/261/contributions/1337/},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@article {2343,
	title = {Automated landmark annotation for morphometric analysis of distal femur and proximal tibia},
	journal = {Journal of Imaging},
	volume = {10},
	year = {2024},
	doi = {10.3390/jimaging10040090 },
	author = {Jonas Grammens and Annemieke Van Haver and Imelda Lumban-Gaol and Femke Danckaers and Peter Verdonk and Jan Sijbers}
}
@article {2323,
	title = {CAD-ASTRA: A versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {3425-3439},
	doi = {https://doi.org/10.1364/OE.498194},
	author = {Pavel Paramonov and Nicholas Francken and Jens Renders and Domenico Iuso and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2419,
	title = {Coherent detection terahertz imaging with a continuous wave source},
	booktitle = {SPIE},
	volume = {13141},
	year = {2024},
	pages = {63-68},
	abstract = {The unique properties of terahertz (THz) radiation, coupled with its non-ionizing nature, enable high-contrast imaging of soft materials with less stringent safety precautions than those required for x-ray systems. In this study, we introduce novel methods for THz imaging using a system that employs two photoconductive antennas (PCAs): one as a Continuous-Wave (CW) source and the other as a coherent detector. To enable precise multiband imaging with high frequency resolution, a fiber stretcher for rapid phase modulation was included. This system allows for the registration of two types of imaging contrasts: light attenuation and phase shift. We outline methods for extracting these contrasts and evaluate the system{\textquoteright}s capabilities through experiments involving various materials and frequencies. Furthermore, its application in computed tomography is demonstrated. To the best of our knowledge, this is the first application of a CW setup based on PCAs for non-destructive inspection and imaging of concealed objects.},
	doi = {https://doi.org/10.1117/12.3027653},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410E/Coherent-detection-terahertz-imaging-with-a-continuous-wave-source/10.1117/12.3027653.short},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2374,
	title = {Deep image prior for sparse-view reconstruction in static, rectangular multi-source x-ray CT systems for cargo scanning},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3027668},
	author = {Caroline Bossuyt and Arnold Jan den Dekker and Domenico Iuso and T. Le Hoang and Julie Escoda and Marius Costin and Jan Sijbers and Jan De Beenhouwer}
}
@article {2360,
	title = {Direct reconstruction of wet foam from sparse-view, dynamic X-ray CT scans},
	journal = {Advanced Engineering Materials},
	volume = {2400957},
	year = {2024},
	pages = {1-10},
	doi = {https://doi.org/10.1002/adem.202400957},
	author = {Jens Renders and Lucia Mancini and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2376,
	title = {Dynamic flat field correction in edge illumination imaging},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3028319},
	author = {Didem G{\"o}kbel Kekliko{\u g}lu and Nicholas Francken and Ben Huyge and Ziya Merdan and Jan De Beenhouwer and Jan Sijbers}
}
@article {2329,
	title = {Edge illumination x-ray phase contrast simulations using the CAD-ASTRA toolbox},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {10005-10021},
	doi = {10.1364/OE.516138},
	url = {https://opg.optica.org/oe/abstract.cfm?doi=10.1364/OE.516138},
	author = {Nicholas Francken and Jonathan Sanctorum and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2413,
	title = {Ensuring Flawlessness in Additive Manufacturing: Advances in X-ray Inspection Techniques for Efficient Defect Detection},
	volume = {PhD in Sciences},
	year = {2024},
	type = {PhD thesis},
	author = {Domenico Iuso}
}
@inproceedings {2375,
	title = {Fast and efficient tetrahedral volume mesh reconstruction with CAD-ASTRA},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	address = {San Diego, USA},
	doi = {https://doi.org/10.1117/12.3027610},
	author = {Jannes Merckx and Arnold Jan den Dekker and Jan De Beenhouwer and Jan Sijbers}
}
@article {2359,
	title = {Foot shape assessment techniques for orthotic and footwear applications: a methodological literature review},
	journal = {Frontiers in Bioengineering and Biotechnology},
	volume = {12},
	year = {2024},
	month = {Sept / 2024},
	pages = {1-15},
	doi = {https://doi.org/10.3389/fbioe.2024.1416499},
	author = {Femke Danckaers and Kristina Stankovi{\'c} and Toon Huysmans and Brian G. Booth and Jan Sijbers}
}
@inproceedings {2350,
	title = {High-resolution tiled X-ray cone-beam CT using the ASTRA toolbox},
	booktitle = {13th Conference on Industrial Computed Tomography (iCT) 2024},
	year = {2024},
	month = {03/2024},
	address = {School of Engineering, Wels Campus, Austria},
	abstract = {Dealing with large and/or elongated objects presents a challenge in micro computed tomography ({\textmu}CT). In conventional CT, the necessity for the X-ray beam to fully cover the scanned object which has to remain well within the detector boundaries is essential to avoid region-of-interest artifacts in the reconstructed images. Consequently, the magnification of the object and thereby the spatial resolution are limited by the physical dimensions and degrees of freedom of the imaging system. A possible way to increase the magnification and thus the resolution of a {\textmu}CT image is to perform a tiled scan of the object. In this paper, we propose an iterative reconstruction approach that yields a high-resolution image from such a tiled CT scan. The approach utilizes the ASTRA toolbox, leveraging its key features: the vector-based definition of projection geometry and the linear tomography operators. Our simulations demonstrate that the proposed approach achieves higher resolution through increased magnification.},
	keywords = {cone beam, iterative reconstruction, micro computed tomography, X-ray tomography},
	isbn = {1435-4934},
	doi = {10.58286/29258 },
	author = {Pavel Paramonov and Joaquim G. Sanctorum and Domenico Iuso and Jan Sijbers and Jan De Beenhouwer}
}
@article {2347,
	title = {Imaging Algorithm and Optimal Measurement Protocol for 3D Impedance Tomography on 2D High Density Micro Electrode Array},
	journal = {IEEE Sensors},
	volume = {24},
	year = {2024},
	pages = {24452-24465},
	doi = {10.1109/JSEN.2024.3417289},
	author = {Jian Deng and Jens Renders and Babu Linkoon P Meenaketan and Saeedeh Ebrahimi Takalloo and Dries Braeken and Jan De Beenhouwer and Jan Sijbers}
}
@mastersthesis {2363,
	title = {Improved 4DCT reconstruction algorithms for the imaging of foam microstructure formation},
	volume = {PhD in Sciences},
	year = {2024},
	type = {PhD thesis},
	author = {Jens Renders}
}
@mastersthesis {2326,
	title = {Improved X-ray CT reconstruction techniques with non-linear imaging models},
	year = {2024},
	type = {PhD thesis},
	author = {Nathana{\"e}l Six}
}
@inproceedings {2468,
	title = {Inline edge illumination through sample mask misalignment: a proof of concept},
	booktitle = {Proceedings of the 6th International Conference on X-ray and Neutron Phase Imaging with Gratings, Shenzhen, China},
	year = {2024},
	abstract = {Edge illumination (EI) is an X-ray phase contrast imaging setup that allows
measuring two additional complimentary contrasts. The setup consists of two absorbing
masks with slit shaped apertures. Typically, one of the masks is stepped during scans,
complicating the application of EI in inline settings. Current solutions exist, but require
either limiting the number of retrieved contrasts or fabricating specialized masks. In this
work, an EI scanning method with purposely misaligned conventional EI masks is
proposed to enable inline EI. Good agreement is found between conventional and inline EI
flatfield parameters, and first inline scan results are presented.},
	keywords = {X-ray phase contrast imaging},
	url = {https://files.sciconf.cn/upload/file/20240415/20240415160406_47435.pdf},
	author = {Nicholas Francken and Jan De Beenhouwer and Jan Sijbers}
}
@article {2348,
	title = {Inline edge illumination X-ray phase contrast imaging through mask misalignment},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {32048-32061},
	doi = {10.1364/OE.525730},
	author = {Nicholas Francken and Jonathan Sanctorum and Joaquim Sanctorum and Pieter-Jan Vanthienen and Jan Sijbers and Jan De Beenhouwer}
}
@article {2321,
	title = {Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {1135-1150},
	doi = {https://doi.org/10.1364/OE.502542},
	author = {Nathana{\"e}l Six and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2381,
	title = {Longitudinal Magnetic Resonance Imaging Method},
	number = {WO2024100240A1},
	year = {2024},
	chapter = {WO2024100240A1},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@article {2467,
	title = {Mask assembly for edge illumination phase contrast radiation imaging},
	number = {EP2025062978W},
	year = {2024},
	month = {11/2025},
	edition = {G01N23/041 },
	chapter = {WO2025237942A1},
	abstract = {In general, the technology disclosed herein relates object inspection utilizing radiation imaging, more specifically, edge illumination phase contrast X-ray imaging. The apparatus and methods described in the present disclosure can be applied for inspection of various objects in different industrial settings, such as manufacturing, food, agriculture, aerospace, automotive, electronics, healthcare, transport, logistics, security, and others. An aspect of the present invention relates to a mask assembly for radiation phase contrast imaging apparatus, comprising a first mask comprising a plurality of X-ray absorbing element and apertures arranged in a manner that gradually diverges from one portion to an opposite portion of the body, resulting in a variable pitch perpendicular to the optical axis direction; and a mask alignment mechanism configured to adjust a position and/or orientation of the first mask to align the variable pitch of the first mask for phase contrast imaging.},
	author = {Jan De Beenhouwer and Jan Sijbers and Pieter-Jan Vanthienen}
}
@article {2380,
	title = {Methods and systems for determining an anatomical reconstruction of a broken bone},
	year = {2024},
	edition = {WO2024068984A1},
	chapter = {PCT/EP2023/077151},
	author = {Jan Sijbers and Femke Danckaers and Jana Osstyn}
}
@article {2325,
	title = {Model-based super-resolution reconstruction for pseudo-continuous Arterial Spin Labeling},
	journal = {NeuroImage},
	volume = {286},
	year = {2024},
	month = {01/2024},
	pages = {120506},
	abstract = {Arterial spin labeling (ASL) is a promising, non-invasive perfusion magnetic resonance imaging technique for quantifying cerebral blood flow (CBF). Unfortunately, ASL suffers from an inherently low signal-to-noise ratio (SNR) and spatial resolution, undermining its potential. Increasing spatial resolution without significantly sacrificing SNR or scan time represents a critical challenge towards routine clinical use. In this work, we propose a model-based super-resolution reconstruction (SRR) method with joint motion estimation that breaks the traditional SNR/resolution/scan-time trade-off. From a set of differently oriented 2D multi-slice pseudo-continuous ASL images with a low through-plane resolution, 3D-isotropic, high resolution, quantitative CBF maps are estimated using a Bayesian approach. Experiments on both synthetic whole brain phantom data, and on in vivo brain data, show that the proposed SRR Bayesian estimation framework outperforms state-of-the-art ASL quantification.},
	keywords = {Arterial spin labeling, CBF mapping, Model-based reconstruction, Perfusion, Quantitative MRI, super-resolution},
	issn = {1053-8119},
	doi = {10.1016/j.neuroimage.2024.120506},
	author = {Quinten Beirinckx and Piet Bladt and Merlijn C E van der Plas and M.J.P van Osch and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {2378,
	title = {Multi-resolution gratings for edge illumination x-ray phase contrast imaging: a simulation study},
	booktitle = {Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	pages = {1315208},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	keywords = {cone-beam, edge illumination, grating design, magnification, mask, monte-carlo, multi-resolution, Phase contrast},
	doi = {10.1117/12.3025968},
	url = {https://doi.org/10.1117/12.3025968},
	author = {Pieter-Jan Vanthienen and Nicholas Francken and Jan Sijbers and Jan De Beenhouwer}
}
@article {2358,
	title = {PACS: Projection-driven with Adaptive CADs X-ray Scatter compensation for additive manufacturing inspection},
	journal = {Precision Engineering},
	volume = {90},
	year = {2024},
	pages = {108-121},
	doi = {https://doi.org/10.1016/j.precisioneng.2024.08.006},
	author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@article {2336,
	title = {Practical multi-mesh registration for few-view poly-chromatic X-ray inspection},
	journal = {Journal of Non-destructive Testing},
	volume = {43},
	year = {2024},
	chapter = {63},
	doi = {10.1007/s10921-024-01071-y},
	author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@conference {2337,
	title = {Reconstruction with rigid motion correction technique in CT imaging: A simulation and application study},
	year = {2024},
	address = {Vietnam Institute for Advanced Study in Mathematics (VIASM), Hanoi, Vietnam},
	author = {Anh-Tuan Nguyen and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2449,
	title = {Simulating Atom Probe Tomography Using MFEM},
	year = {2024},
	abstract = {In atom probe tomography (APT), spatial reconstruction enables volumetric insight into a specimen{\textquoteright}s nanostructure. To this day, a fast reconstruction method which utilizes the true potential of APT in terms of resolution does not exist. A model of its effective inverse, the field evaporation, which provides a physically accurate description of the ion trajectories, is a crucial component in reconstruction. The simulation of each individual evaporation while has been time inefficient. We introduce AdAPTS, an adaptive atom probe tomography simulation library based on MFEM. AdAPTS is capable of generating accurate detector hit maps of various specimens, efficiently representing and simulating the experimental domain from specimen to detector. Using AdAPTS, we are able to accurately simulate the field evaporation of various specimens, revealing realistic poles and zone lines. },
	url = {https://mfem.org/workshop24/$\#$agenda},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2466,
	title = {A simulation study of optimized-aperture gratings for edge illumination cone-beam phase contrast x-ray imaging},
	booktitle = {Proceedings of the 6th International Conference on X-ray and Neutron Phase Imaging with Gratings},
	year = {2024},
	month = {04/2024},
	address = {Shenzhen, China},
	abstract = {Edge illumination (EI) is an established x-ray phase-contrast imaging method that relies on gratings to obtain attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone-beam geometry of lab systems limits the effectiveness of conventional gratings. The non-parallel incidence of X-rays on planar gratings with equally sized apertures introduces unwanted shadowing effects. In this paper, a grating design with optimized position-dependent apertures is introduced and compared to a conventional grating and a grating with fan-beam shaped gratings bars. Numerical simulations show that this optimized-aperture design must be considered when constructing an EI setup.},
	author = {Pieter-Jan Vanthienen and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2327,
	title = {Statistical shape model guided virtual reduction of displaced distal radius fractures},
	booktitle = {IEEE International Symposium on Biomedical Imaging},
	year = {2024},
	pages = {1-5},
	address = {Athens, Greece},
	doi = {10.1109/ISBI56570.2024.10635672},
	author = {Jana Osstyn and Femke Danckaers and A Verstreken and Annemieke Van Haver and Matthias Vanhees and Jan Sijbers}
}
@article {2355,
	title = {Three-dimensional bone morphology is a risk factor for medial postmeniscectomy syndrome: A retrospective cohort study},
	journal = {Journal of Experimental Orthopaedics},
	volume = {11},
	year = {2024},
	pages = {e12090},
	doi = {https://doi.org/10.1002/jeo2.12090},
	author = {Jonas Grammens and Annemieke Van Haver and Femke Danckaers and Kristien Vuylsteke and Jan Sijbers and Lotem Mahluf and Peter Angele and Elizaveta Kon and Peter Verdonk}
}
@article {2349,
	title = {Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models},
	journal = {Applied Intelligence},
	volume = {54},
	year = {2024},
	pages = { 13160{\textendash}13177},
	doi = {https://doi.org/10.1007/s10489-024-05647-z},
	author = {Domenico Iuso and Soumick Chatterjee and Sven Cornelissen and Dries Verhees and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2373,
	title = {X-ray image reconstruction for continuous acquisition with accelerated rotation},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3027622},
	author = {Ben Huyge and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2365,
	title = {X-ray image reconstruction for continuous acquisitions with a generalized motion model},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {39192-39207},
	doi = {https://doi.org/10.1364/OE.531999},
	author = {Ben Huyge and Jens Renders and Joaquim Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2333,
	title = {Acritical Comparison of Linear and Nonlinear Unmixing for Intimate Mixtures},
	booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
	year = {2023},
	pages = {1-5},
	keywords = {Conferences, Estimation, hyperspectral image, Hyperspectral imaging, intimate mixtures, linear and nonlinear unmixing, Powders, Reflectivity, Signal processing, Spectroradiometers},
	doi = {10.1109/WHISPERS61460.2023.10431354},
	author = {Koirala, Bikram and Das, Samiran and Rasti, Behnood and Ghamisi, Pedram and Gloaguen, Richard and Paul Scheunders}
}
@inproceedings {2295,
	title = {Adapting an XCT-scanner to enable edge illumination X-ray phase contrast imaging},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934},
	doi = {doi.org/10.58286/27755},
	author = {Ben Huyge and Pieter-Jan Vanthienen and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@article {2256,
	title = {ADEPT: Accurate Diffusion EPI with multi-contrast shoTs},
	journal = {Magnetic Resonance in Medicine},
	volume = {89},
	year = {2023},
	pages = {396-410},
	doi = {10.1002/mrm.29398},
	author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Stefan Klein and Johan Van Audekerke and Verhoye, Marleen and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {2282,
	title = {Automated virtual reduction of displaced distal radius fractures},
	booktitle = {IEEE International Symposium on Biomedical Imaging},
	year = {2023},
	pages = {1-4},
	address = {Cartagena, Colombia},
	doi = {10.1109/ISBI53787.2023.10230399},
	author = {Jana Osstyn and Femke Danckaers and Annemieke Van Haver and Jose Oramas and Matthias Vanhees and Jan Sijbers}
}
@inproceedings {2352,
	title = {Comparison of diffusion kurtosis tensor imaging and multi-tissue CSD for the investigation of group differences in Alzheimer{\textquoteright}s disease},
	booktitle = {International Society of Magnetic Resonance in Medicine (ISMRM)},
	year = {2023},
	address = {Toronto, ON, Canada},
	url = {https://submissions.mirasmart.com/ISMRM2023/Itinerary/PresentationDetail.aspx?evdid=6363},
	author = {Diana Giraldo and Robert E. Smith and Hanne Struyfs and Ellis Niemantsverdriet and Ellen De Roeck and Maria Bjerke and Sebastiaan Engelborghs and Eduardo Romero and Jan Sijbers and Ben Jeurissen}
}
@inproceedings {2287,
	title = {A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations},
	booktitle = {45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
	year = {2023},
	author = {Nicholas Francken and Jonathan Sanctorum and Jens Renders and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2292,
	title = {The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis},
	booktitle = {31st European Signal Processing Conference, EUSIPCO},
	year = {2023},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2293,
	title = {Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934 },
	doi = {doi.org/10.58286/27716},
	author = {Miroslav Yosifov and Patrick Weinberger and Michael Reiter and Bernhard Fr{\"o}hler and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2283,
	title = {DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data},
	booktitle = {IEEE International Symposium on Biomedical Imaging},
	year = {2023},
	pages = {1-4},
	doi = {10.1109/ISBI53787.2023.10230697},
	author = {Jens Renders and Banafshe Shafieizargar and Marleen Verhoye and Jan De Beenhouwer and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2305,
	title = {Efficient iterative reconstruction with beam shape compensation for THz computed tomography},
	journal = {Applied Optics},
	volume = {62},
	year = {2023},
	month = {April 14, 2023},
	pages = {F31-F40},
	chapter = {F31},
	abstract = {Terahertz (THz) computed tomography is an emerging nondestructive and non-ionizing imaging method. Most THz reconstruction methods rely on the Radon transform, originating from x-ray imaging, in which x rays propagate in straight lines. However, a THz beam has a finite width, and ignoring its shape results in blurred reconstructed images. Moreover, accounting for the THz beam model in a straightforward way in an iterative reconstruction method results in extreme demands in memory and in slow convergence. In this paper, we propose an efficient iterative reconstruction that incorporates the THz beam shape, while avoiding the above disadvantages. Both simulation and real experiments show that our approach results in improved resolution recovery in the reconstructed image. Furthermore, we propose a suitable preconditioner to improve the convergence speed of our reconstruction.},
	keywords = {Beam shaping, computed tomography, Image quality, image reconstruction, THz imaging},
	doi = {https://doi.org/10.1364/AO.482511},
	url = {https://opg.optica.org/viewmedia.cfm?r=1\&rwjcode=ao\&uri=ao-62-17-F31\&seq=0},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2299,
	title = {Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations},
	booktitle = {IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy},
	year = {2023},
	author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2317,
	title = {An Extensive Multisensor Hyperspectral Benchmark Datasets of Intimate Mixtures of Mineral Powders},
	booktitle = { IEEE International Geoscience and Remote Sensing Symposium},
	year = {2023},
	month = {20 October 2023},
	pages = {5890-5893},
	abstract = {Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain.In this work, we generated a comprehensive hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets)},
	doi = {10.1109/IGARSS52108.2023.10281467},
	author = {Bikram Koirala and Behnood Rasti and Zakaria Bnoulkacem and Andr{\'e}a De Lima Ribeiro and Yuleika Madriz and Erik Herrmann and Arthur Gestels and Thomas De Kerf and Koen Janssens and Gunther Steenackers and Richard Gloaguen and Paul Scheunders}
}
@article {2264,
	title = {Fast and accurate pose estimation of additive manufactured objects from few X-ray projections},
	journal = {Expert Systems With Applications},
	volume = {213},
	year = {2023},
	pages = {1-10},
	doi = {https://doi.org/10.1016/j.eswa.2022.118866},
	author = {Alice Presenti and Liang, Zhihua and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2298,
	title = {Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution},
	journal = {Polymers},
	volume = {15},
	year = {2023},
	pages = {2887},
	doi = {https://doi.org/10.3390/polym15132887},
	author = {Ben Huyge and Jonathan Sanctorum and Ben Jeurissen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2446,
	title = {Fitting a 2D mesh to X-ray measurements},
	booktitle = { 			 17th International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2023},
	address = {Stony Brook},
	author = {Merckx, Jannes and Jan Sijbers and Jan De Beenhouwer}
}
@article {2301,
	title = {Grating designs for cone beam edge illumination X-ray phase contrast imaging: a simulation study},
	journal = {Optics Express},
	volume = {31},
	year = {2023},
	pages = {28051-28064},
	abstract = {Edge illumination is an emerging X-ray phase contrast imaging technique providing attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone beam geometry of lab systems limits the effectiveness of using conventional planar gratings. The non-parallel incidence of X-rays introduces shadowing effects, worsening with increasing cone angle. To overcome this limitation, several alternative grating designs can be considered. In this paper, the effectiveness of three alternative designs is compared to conventional gratings using numerical simulations. Improvements in flux and contrast are discussed, taking into account practical considerations concerning the implementation of the designs.},
	doi = {10.1364/OE.495789},
	url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-17-28051\&id=536127},
	author = {Pieter-Jan Vanthienen and Jonathan Sanctorum and Ben Huyge and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2339,
	title = {Hyperspectral imaging for automated inspection of offshore wind infrastructure},
	year = {2023},
	type = {PhD thesis},
	author = {Thomas De Kerf}
}
@article {2304,
	title = {ImWIP: open-source image warping toolbox with adjoints and derivatives},
	journal = {SoftwareX},
	volume = {24},
	year = {2023},
	pages = {101524},
	doi = {https://doi.org/10.1016/j.softx.2023.101524},
	author = {Jens Renders and Ben Jeurissen and Anh-Tuan Nguyen and Jan De Beenhouwer and Jan Sijbers}
}
@article {2324,
	title = {A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures},
	journal = {IEEE Sensors Journal},
	year = {2023},
	month = {2023/12/28},
	abstract = {Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. 

In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets.},
	author = {Bikram Koirala and Behnood Rasti and Zakaria Bnoulkacem and Andr{\'e}a De Lima Ribeiro and Yuleika Madriz and Erik Herrmann and Arthur Gestels and Thomas De Kerf and Sandra Lorenz and Margret Fuchs and Koen Janssens and Gunther Steenackers and Richard Gloaguen and Paul Scheunders}
}
@article {2274,
	title = {Optimal experimental design and estimation for q-space trajectory imaging},
	journal = {Human Brain Mapping},
	volume = {44},
	year = {2023},
	pages = {1793-1809},
	abstract = {Tensor-valued diffusion encoding facilitates data analysis by q-space trajectory imaging. By modeling the diffusion signal of heterogeneous tissues with a diffusion tensor distribution (DTD) and modulating the encoding tensor shape, this novel approach allows disentangling variations in diffusivity from microscopic anisotropy, orientation dispersion, and mixtures of multiple isotropic diffusivities. To facilitate the estimation of the DTD parameters, a parsimonious acquisition scheme coupled with an accurate and precise estimation of the DTD is needed. In this work, we create two precision-optimized acquisition schemes: one that maximizes the precision of the raw DTD parameters, and another that maximizes the precision of the scalar measures derived from the DTD. The improved precision of these schemes compared to a naive sampling scheme is demonstrated in both simulations and real data. Furthermore, we show that the weighted linear least squares (WLLS) estimator that uses the squared reciprocal of the noisy signal as weights can be biased, whereas the iteratively WLLS estimator with the squared reciprocal of the predicted signal as weights outperforms the conventional unweighted linear LS and nonlinear LS estimators in terms of accuracy and precision. Finally, we show that the use of appropriate constraints can considerably increase the precision of the estimator with only a limited decrease in accuracy.},
	doi = {10.1002/hbm.26175},
	author = {Jan Morez and Szczepankiewicz, Filip and Arnold Jan den Dekker and Floris Vanhevel and Jan Sijbers and Ben Jeurissen}
}
@mastersthesis {2290,
	title = {Parametric Fiber Analysis for Glass Fiber-reinforced Composite Tomographic Images},
	year = {2023},
	type = {PhD thesis},
	author = {Tim Elberfeld}
}
@article {2270,
	title = {Prolonged microgravity induces reversible and persistent changes on human cerebral connectivity},
	journal = {Communications Biology},
	volume = {6},
	year = {2023},
	doi = {https://doi.org/10.1038/s42003-022-04382-w},
	author = {Steven Jillings and Ekaterina V. Pechenkova and Elena Tomilovskaya and Ilya Rukavishnikov and Ben Jeurissen and Angelique Van Ombergen and Nosikova, Inna and Alena Rumshiskaya and Liudmila Litvinova and Annen, Jitka and Chloe De Laet and Catho Schoenmaekers and Jan Sijbers and Petrovichev, Victor and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and zu Eulenburg, P and Steven S L Laureys and Athena Demertzi and Floris L Wuyts}
}
@article {2306,
	title = {A reconstruction method for atom probe tomography},
	number = {18017575},
	year = {2023},
	edition = {US20230307207A1},
	chapter = {US Patent App. 18/017,575, 2023},
	author = {Jan Sijbers and Jan De Beenhouwer and Yu-Ting Ling and Wilfried Vandervorst}
}
@inproceedings {2279,
	title = {Region-based motion-compensated iterative reconstruction technique for dynamic computed tomography},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2023},
	address = {Cartagena de Indias, Colombia},
	doi = {https://doi.org/10.1109/ISBI53787.2023.10230608},
	author = {Anh-Tuan Nguyen and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2281,
	title = {Sparse-view Medical Tomosynthesis via Mixed Scale Dense Convolutional Framelet Networks},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2023},
	pages = {880-884},
	doi = { https://doi.org/10.23919/EUSIPCO58844.2023.10289781},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2288,
	title = {Super-resolution reconstruction of multi-slice T2-w FLAIR MRI improves Multiple Sclerosis lesion segmentation},
	booktitle = {45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
	year = {2023},
	address = {Sydney, Australia},
	abstract = {Due to acquisition time constraints, T2-w FLAIR MRI of Multiple Sclerosis (MS) patients is often acquired with multi-slice 2D protocols with a low through-plane resolution rather than with high-resolution 3D protocols. Automated lesion segmentation on such low-resolution (LR) images, however, performs poorly and leads to inaccurate lesion volume estimates. Super-resolution reconstruction (SRR) methods can then be used to obtain a high-resolution (HR) image from multiple LR images to serve as input for lesion segmentation. In this work, we evaluate the effect on MS lesion segmentation of three SRR approaches: one based on interpolation, a state-of-the-art self-supervised CNN-based strategy, and a recently proposed model-based SRR method. These SRR strategies were applied to LR acquisitions simulated from 3D T2-w FLAIR MRI of MS patients. Each SRR method was evaluated in terms of image reconstruction quality and posterior lesion segmentation performance. When compared to segmentation on LR images, the three considered SRR strategies demonstrate improved lesion segmentation. Furthermore, in some scenarios, SRR achieves a similar segmentation performance compared to segmentation of HR images.},
	author = {Diana Giraldo and Quinten Beirinckx and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@article {2289,
	title = {Systematic review of reconstruction techniques for accelerated quantitative MRI},
	journal = {Magnetic Resonance in Medicine},
	volume = {90},
	year = {2023},
	pages = {1172-1208},
	doi = {https://doi.org/10.1002/mrm.29721},
	author = {Banafshe Shafieizargar and Riwaj Byanju and Jan Sijbers and Stefan Klein and Arnold Jan den Dekker and Dirk H J Poot}
}
@article {2255,
	title = {Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction},
	journal = {The Visual Computer},
	volume = {39},
	year = {2023},
	pages = {4671{\textendash}4683},
	doi = {10.1007/s00371-022-02616-w},
	author = {Daniel Frenkel and Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2294,
	title = {Toward denoising of 3D CT scans with few data},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934},
	doi = {doi.org/10.58286/27741},
	author = {Liang, Zhihua and Anneke Van Heteren and Jan Sijbers and Jan De Beenhouwer}
}
@article {2286,
	title = {Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study},
	journal = {Journal of Neurotrauma},
	volume = {40},
	year = {2023},
	pages = {1317-1338},
	doi = {https://doi.org/10.1089/neu.2022.0365},
	author = {Maira Siqueira Pinto and Stefan Winzeck and Evgenios N. Kornaropoulos and Sophie Richter and Roberto Paolella and Marta M. Correia and Ben Glocker and Guy Williams and Anne Vik and Jussi Posti and Asta Kristine H{\r a}berg and Jonas Stenberg and Pieter-Jan Guns and Arnold Jan den Dekker and David K. Menon and Jan Sijbers and Pieter Van Dyck and Virginia F. J. Newcombe}
}
@article {2204,
	title = {3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts},
	journal = {Measurement Science and Technology},
	volume = {33},
	year = {2022},
	pages = {1-12},
	doi = {10.1088/1361-6501/ac459a},
	author = {Rob Heylen and Aditi Thanki and Dries Verhees and Domenico Iuso and Jan De Beenhouwer and Jan Sijbers and Ann Witvrouw and Han Haitjema and Abdellatif Bey-Temsamani}
}
@mastersthesis {2280,
	title = {3D X-ray radiography-based inspection of manufactured objects},
	volume = {PhD},
	year = {2022},
	type = {PhD thesis},
	author = {Alice Presenti}
}
@inproceedings {2239,
	title = {An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography},
	booktitle = {Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F},
	year = {2022},
	address = {San Diego, CA, United States},
	doi = {https://doi.org/10.1117/12.2631570},
	author = {Anh-Tuan Nguyen and Jens Renders and Jeroen Soete and Martine Wevers and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2268,
	title = {Adaptive triangular mesh for phase contrast imaging},
	year = {2022},
	url = {https://ictms2022.sciencesconf.org/385325/document},
	author = {Jannes Merckx and Bart van Lith and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2278,
	title = {Advances in biplanar X-ray imaging: calibration and 2D/3D registration},
	volume = {PhD},
	year = {2022},
	type = {PhD thesis},
	author = {Van Nguyen}
}
@inproceedings {2262,
	title = {Alternative grating designs for cone-beam edge illumination X-ray phase contrast imaging},
	booktitle = { Proc. SPIE 12242, Developments in X-Ray Tomography XIV},
	volume = {12242},
	year = {2022},
	month = {10/2022},
	pages = {122420Z},
	publisher = {SPIE},
	organization = {SPIE},
	address = {San Diego, USA},
	doi = {10.1117/12.2632301},
	author = {Pieter-Jan Vanthienen and Jonathan Sanctorum and Ben Huyge and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2227,
	title = {Analysis of Plant Stress Response Using Hyperspectral Imaging and Kernel Ridge Regression},
	booktitle = {11th International Conference on Robotics, Vision, Signal Processing and Power Applications},
	volume = {829},
	year = {2022},
	publisher = {Lecture Notes in Electrical Engineering, Springer},
	organization = {Lecture Notes in Electrical Engineering, Springer},
	address = {Singapore},
	doi = {10.1007/978-981-16-8129-5_66},
	author = {Mohd Shahrimie Mohd Asaari and Stien Mertens and Stijn Dhondt and Dirk Inze and Paul Scheunders}
}
@inproceedings {2192,
	title = {Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = { 27 (3)},
	year = {2022},
	pages = {1-5},
	doi = {https://doi.org/10.58286/26588},
	url = {https://www.ndt.net/search/docs.php3?id=26588},
	author = {Anh-Tuan Nguyen and Jens Renders and Jeroen Soete and Martine Wevers and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2237,
	title = {Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?},
	booktitle = {Proc. SPIE 12242, Developments in X-Ray Tomography XIV},
	year = {2022},
	month = {10/2022},
	pages = {1224218},
	publisher = {SPIE},
	organization = {SPIE},
	address = {San Diego, USA},
	doi = {10.1117/12.2633455},
	author = {Jonathan Sanctorum and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@article {2236,
	title = {Automatic anomaly detection from X-ray images based on autoencoder},
	journal = {Nondestructive Testing and Evaluation},
	volume = {37},
	year = {2022},
	doi = {10.1080/10589759.2022.2074415},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2257,
	title = {Automatic landmark detection and mapping for 2D/3D registration with BoneNet},
	journal = {Frontiers Veterinary Science},
	year = {2022},
	doi = {https://doi.org/10.3389/fvets.2022.923449},
	author = {Van Nguyen and Luis Filipe Alves Pereira and Liang, Zhihua and Falk Mielke and Jeroen Van Houtte and Jan Sijbers and Jan De Beenhouwer}
}
@article {2212,
	title = {A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography},
	journal = {Microscopy and Microanalysis},
	volume = {28},
	year = {2022},
	pages = {1-14},
	doi = {10.1017/S1431927621012836},
	author = {Yu-Ting Ling and Siegfried Cools and Janusz Bogdanowicz and Claudia Fleischmann and Jan De Beenhouwer and Jan Sijbers and Wilfried Vandervorst}
}
@article {2216,
	title = {Brain Connectometry Changes in Space Travelers After Long-Duration Spaceflight},
	journal = {Front. Neural Circuits},
	volume = {16},
	year = {2022},
	doi = {https://doi.org/10.3389/fncir.2022.815838},
	author = {Andrei Doroshin and Steven Jillings and Ben Jeurissen and Elena Tomilovskaya and Ekaterina V. Pechenkova and Nosikova, Inna and Alena Rumshiskaya and Liudmila Litvinova and Ilya Rukavishnikov and Chloe De Laet and Catho Schoenmaekers and Jan Sijbers and Steven S L Laureys and Petrovichev, Victor and Angelique Van Ombergen and Jitka Annen and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and zu Eulenburg, Peter and Karol Osipowicz and Floris L Wuyts}
}
@inproceedings {2194,
	title = {CNN-based pose estimation from a single X-ray projection for 3D inspection of manufactured objects},
	booktitle = {11th Conference on Industrial Computed Tomography},
	year = {2022},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2276,
	title = {cuPARE: Parametric Reconstruction of Curved Fibres from Glass fibre-reinforced Composites},
	journal = {Nondestructive Testing and Evaluation},
	year = {2022},
	doi = {10.1080/10589759.2022.2155647},
	author = {Tim Elberfeld and Bernhard Fr{\"o}hler and Christoph Heinzl and Jan Sijbers and Jan De Beenhouwer}
}
@article {2193,
	title = {Discrete Terahertz tomography: a simulation study},
	journal = {e-Journal of Nondestructive Testing},
	volume = {27},
	year = {2022},
	issn = {1435-4934},
	doi = {doi.org/10.58286/26608},
	author = {Jana Christopher and Lars-Paul Lumbeeck and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@conference {2269,
	title = {Edge Illumination Phase Contrast Simulations Using the OptiX GPU Ray Tracing Engine},
	year = {2022},
	author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@article {2215,
	title = {The effect of prolonged Spaceflight on Cerebrospinal Fluid and Perivascular Spaces of Astronauts and Cosmonauts},
	journal = {PNAS},
	volume = {119},
	year = {2022},
	chapter = {e2120439119},
	doi = {https://doi.org/10.1073/pnas.2120439119},
	author = {Giuseppe Barisano and Farshid Sepehrband and Heather R. Collins and Steven Jillings and Ben Jeurissen and Andrew J. Taylor and Catho Schoenmaekers and Chloe De Laet and Ilya Rukavishnikov and Inna Nosikova and Alena Rumshiskaya and Jitka Annen and Jan Sijbers and Steven S L Laureys and Angelique Van Ombergen and Petrovichev, Victor and Valentin Sinitsyn and Ekaterina V. Pechenkova and Alexey Grishin and Peter zu Eulenburg and Meng Law and Stefan Sunaert and Paul M. Parizel and Elena Tomilovskaya and Donna Roberts and Floris L Wuyts}
}
@inproceedings {2240,
	title = {Efficient X-ray projection of triangular meshes based on ray tracing and rasterization},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122420W },
	doi = {https://doi.org/10.1117/12.2633448},
	author = {Pavel Paramonov and Jens Renders and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2243,
	title = {Evaluation of deeply supervised neural networks for 3D pore segmentation in additive manufacturing},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122421K},
	doi = {https://doi.org/10.1117/12.2633318},
	author = {Domenico Iuso and Soumick Chatterjee and Rob Heylen and Sven Cornelissen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2272,
	title = {Fiber orientation estimation by constrained spherical deconvolution of the anisotropic edge illumination x-ray dark field signal},
	booktitle = {SPIE: Developments in X-Ray Tomography XIV},
	volume = {12242},
	year = {2022},
	pages = {122420V },
	doi = {ttps://doi.org/10.1117/12.2633482},
	author = {Ben Huyge and Ben Jeurissen and Jan De Beenhouwer and Jan Sijbers}
}
@article {2208,
	title = {Identification of corrosion minerals usning shortwave infrared hyperspectral imaging},
	journal = {Sensors},
	volume = {22},
	year = {2022},
	pages = {407},
	abstract = {In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900{\textendash}1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time. },
	author = {Thomas De Kerf and G. Pipintakos and Zohreh Zahiri and Steve Vanlanduit and Paul Scheunders}
}
@article {2235,
	title = {Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model},
	journal = {NeuroImage},
	volume = {256},
	year = {2022},
	pages = {119219},
	doi = {https://doi.org/10.1016/j.neuroimage.2022.119219},
	author = {Vincenzo Anania and Quinten Collier and Jelle Veraart and Annemieke Eline Buikema and Floris Vanhevel and Thibo Billiet and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2265,
	title = {Investigating tissue-specific abnormalities in Alzheimer{\textquoteright}s disease with multi-shell diffusion MRI},
	journal = {Journal of Alzheimer{\textquoteright}s Disease},
	volume = {90},
	year = {2022},
	pages = {1771-1791},
	doi = {10.3233/JAD-220551},
	author = {Diana Giraldo and Robert Elton Smith and Hanna Struyfs and Ellis Niemantsverdriet and Ellen De Roeck and Maria Bjerke and Sebastiaan Engelborghs and Romero, Eduardo and Jan Sijbers and Ben Jeurissen}
}
@inproceedings {2242,
	title = {Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122420O},
	doi = {https://doi.org/10.1117/12.2633587},
	author = {Nathana{\"e}l Six and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2247,
	title = {Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping},
	journal = {Computerized Medical Imaging and Graphics},
	volume = {100},
	year = {2022},
	month = {09/2022},
	pages = {1-16},
	chapter = {102071},
	abstract = {Quantitative Magnetic Resonance (MR) imaging provides reproducible measurements of biophysical parameters, and has become an essential tool in clinical MR studies. Unfortunately, 3D isotropic high resolution (HR) parameter mapping is hardly feasible in clinical practice due to prohibitively long acquisition times. Moreover, accurate and precise estimation of quantitative parameters is complicated by inevitable subject motion, the risk of which increases with scanning time. In this paper, we present a model-based super-resolution reconstruction (SRR) method that jointly estimates HR quantitative parameter maps and inter-image motion parameters from a set of 2D multi-slice contrast-weighted images with a low through-plane resolution. The method uses a Bayesian approach, which allows to optimally exploit prior knowledge of the tissue and noise statistics. To demonstrate its potential, the proposed SRR method is evaluated for a T1 and T2 quantitative mapping protocol. Furthermore, the method{\textquoteright}s performance in terms of precision, accuracy, and spatial resolution is evaluated using simulated as well as real brain imaging experiments. Results show that our proposed fully flexible, quantitative SRR framework with integrated motion estimation outperforms state-of-the-art SRR methods for quantitative MRI.},
	issn = {0895-6111},
	doi = {https://doi.org/10.1016/j.compmedimag.2022.102071},
	author = {Quinten Beirinckx and Ben Jeurissen and Michele Nicastro and Dirk H J Poot and Marleen Verhoye and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2409,
	title = {Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress},
	journal = {Computers and Electronics in Agriculture},
	volume = {195},
	year = {2022},
	pages = {106806},
	abstract = {Conventional methods to access plant physiological traits are based on destructive measurements by means of biochemical extraction or leaf clipping, thereby limiting the throughput capability. With advances in hyperspectral imaging sensor, fast, non-invasive and non-destructive measurements of a plant{\textquoteright}s physiological status became feasible. In this work, a non-destructive method for the characterization of a plant{\textquoteright}s status from hyperspectral images is presented. A supervised data-driven method based on Machine Learning Regression (MLR) algorithms was developed to generate prediction models of four targeted physiological traits: water potential, effective quantum yield of photosystem II, transpiration rate and stomatal conductance. Standard Normal Variate (SNV) transformed reflectance spectra were used as the input variables for building the regression model. Three MLR algorithms: Gaussian Process Regression (GPR), Kernel Ridge Regression (KRR), and Partial Least Squares Regression (PLSR) were explored as candidate methods for building the prediction model of the targeted physiological traits. Validation results show that the non-linear prediction models, developed based on the GPR algorithm produced the best estimation accuracy on all plant traits. The best prediction models were applied to a small-scale phenotyping experiment to study drought stress responses in maize plants. Results show that all estimated traits revealed a significant difference between plants under drought stress and normal growth dynamics as early as after 3 days of drought induction.},
	keywords = {Drought stress, Hyperspectral imaging, Machine learning regression, Non-destructive measurements, Physiological traits, Plant phenotyping},
	issn = {0168-1699},
	doi = {https://doi.org/10.1016/j.compag.2022.106806},
	url = {https://www.sciencedirect.com/science/article/pii/S0168169922001235},
	author = {Mohd Shahrimie Mohd Asaari and Stien Mertens and Lennart Verbraeken and Stijn Dhondt and Dirk Inze and Koirala Bikram and Paul Scheunders}
}
@article {2221,
	title = {Non-Destructive Analysis of Plant Physiological Traits Using Hyperspectral Imaging: A Case Study on Drought Stress},
	journal = {Computers and Electronics in Agriculture},
	volume = {195},
	year = {2022},
	doi = {10.1016/j.compag.2022.106806},
	author = {Mohd Shahrimie Mohd Asaari and Stien Mertens and Lennart Verbraeken and Stijn Dhondt and Dirk Inze and Bikram Koirala and Paul Scheunders}
}
@conference {2233,
	title = {Optimal acquisition settings for simultaneous diffusion kurtosis, free water fraction and T2 estimation},
	year = {2022},
	author = {Vincenzo Anania and Ben Jeurissen and Jan Morez and Annemieke Eline Buikema and Thibo Billiet and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {2241,
	title = {Optimization of a multi-source rectangular X-ray CT geometry for inline inspection},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {1224219 },
	doi = {https://doi.org/10.1117/12.2633523},
	author = {Caroline Bossuyt and Jan De Beenhouwer and Jan Sijbers}
}
@article {2246,
	title = {Probability of Detection applied to X-ray inspection using numerical simulations},
	journal = {Nondestructive Testing and Evaluation},
	volume = {37},
	year = {2022},
	pages = {536-551},
	doi = {10.1080/10589759.2022.2071892},
	author = {Miroslav Yosifov and M. Reiter and S. Heupl and C. Gusenbauer and Bernhard Fr{\"o}hler and R. Fernandez- Gutierrez and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@article {2403,
	title = {Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging},
	journal = {RSC Advances},
	volume = {12},
	year = {2022},
	pages = {32775-32783},
	author = {Thomas De Kerf and Arthur Gestels and Janssens, Koen and Gunther Steenackers and Paul Scheunders and Steve Vanlanduit}
}
@conference {2217,
	title = {Sparse view rectangular X-ray CT for cargo inspection using the ASTRA toolbox},
	year = {2022},
	author = {Caroline Bossuyt and Jan De Beenhouwer and Jan Sijbers}
}
@article {2249,
	title = {The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget{\textquoteright}s disease of bone?},
	journal = {Bone Reports},
	volume = {16},
	year = {2022},
	pages = {75-76},
	doi = {10.1016/j.bonr.2022.101483},
	author = {Yentl Huybrechts and Rapha{\"e}l De Ridder and Bjorn De Samber and Eveline Boudin and Francesca Tonelli and Dries Knapen and Dorien Schepers and Jan De Beenhouwer and Jan Sijbers and Antonella Forlino and Paul Coucke and P. Eckhard Witten and Ronald Kwon and Andy Willaert and Gretl Hendrickx and Wim Van Hul}
}
@article {2275,
	title = {To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging},
	journal = {Frontiers in Neuroscience},
	year = {2022},
	pages = {1-18},
	doi = {https://doi.org/10.3389/fnins.2022.1044510},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@article {2263,
	title = {Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging},
	journal = {Optics Express},
	volume = {31},
	year = {2022},
	pages = {38695-38708},
	doi = {https://doi.org/10.1364/OE.472145},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2170,
	title = {3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior},
	year = {2021},
	author = {Shiva Hosseinnejad and E. G. T. Bosch and H. Kohr and I. Lazi{\'c} and V. Zharinov and E. Franken and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2186,
	title = {3D THz Tomography Incorporating the Beam Shape},
	booktitle = {2021 OSA Imaging and Applied Optics Congress},
	year = {2021},
	doi = {10.1364/AIS.2021.JTu5A.36},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2184,
	title = {Accelerated multi-shot diffusion weighted imaging with joint estimation of diffusion and phase parameters},
	volume = {34},
	year = {2021},
	pages = {S57-S58},
	doi = {10.1007/s10334-021-00947-8},
	author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Johan Van Audekerke and Marleen Verhoye and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2144,
	title = {Adjoint image warping using multivariate splines with application to 4D-CT},
	journal = {Medical Physics},
	volume = {48},
	year = {2021},
	pages = {6362-6374},
	doi = {10.1002/mp.14765},
	author = {Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2098,
	title = {Analysis of flat fields in edge illumination phase contrast imaging},
	booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
	year = {2021},
	pages = {1310-1313},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Nice, France},
	doi = {10.1109/ISBI48211.2021.9433849},
	url = {https://ieeexplore.ieee.org/document/9433849},
	author = {Ben Huyge and Jonathan Sanctorum and Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2172,
	title = {CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts},
	booktitle = {IEEE ICIP},
	year = {2021},
	pages = {2948-2952},
	doi = {10.1109/ICIP42928.2021.9506536},
	author = {Domenico Iuso and Ehsan Nazemi and Nathana{\"e}l Six and Bjorn De Samber and Jan De Beenhouwer and Jan Sijbers}
}
@inbook {2154,
	title = {Chapter Eight - General conclusions and future perspectives},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Eight - General conclusions and future perspectives},
	doi = {10.1016/bs.aiep.2021.01.008},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2152,
	title = {Chapter Five - Optimal experiment design for nanoparticle atom counting from ADF STEM images},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Five - Optimal experiment design for nanoparticle atom counting from ADF STEM images},
	doi = {10.1016/bs.aiep.2021.01.005},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2150,
	title = {Chapter Four - Atom counting},
	booktitle = {Advances in Imaging and Electron Physics,},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Four - Atom counting},
	doi = {10.1016/bs.aiep.2021.01.004},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2149,
	title = {Chapter One - Introduction},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {One-introduction},
	doi = {10.1016/bs.aiep.2021.01.001},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2153,
	title = {Chapter Seven - Image-quality evaluation and model selection with maximum a posteriori probability},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Seven - Image-quality evaluation and model selection with maximum a posteriori probability},
	doi = {10.1016/bs.aiep.2021.01.007},
	author = {Jarmo Fatermans and Annick De Backer and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2156,
	title = {Chapter Six - Atom column detection},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Six - Atom column detection},
	doi = {10.1016/bs.aiep.2021.01.006},
	author = {Jarmo Fatermans and Annick De Backer and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2155,
	title = {Chapter Three - Efficient fitting algorithm},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Three - Efficient fitting algorithm},
	doi = {10.1016/bs.aiep.2021.01.003},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inbook {2151,
	title = {Chapter Two - Statistical parameter estimation theory: principles and simulation studies},
	booktitle = {Advances in Imaging and Electron Physics},
	volume = {217},
	year = {2021},
	publisher = {Science Direct Elsevier},
	organization = {Science Direct Elsevier},
	chapter = {Chapter Two - Statistical parameter estimation theory: principles and simulation studies},
	doi = {10.1016/bs.aiep.2021.01.002},
	author = {Annick De Backer and Jarmo Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inproceedings {2201,
	title = {CNN-based Pose Estimation of Manufactured Objects During Inline X-ray Inspection},
	booktitle = {2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)},
	year = {2021},
	abstract = {X-ray Computed Tomography (CT) is a nondestructive technique widely used for inspection of manufactured objects generated from a reference computer-aided-design (CAD) representation. In a conventional CT inspection framework, a volumetric reconstruction is computed from a large number of X-ray projections of the object. Afterwards, a surface is extracted, aligned and compared to the CAD model. For an accurate comparison, a high-resolution reconstruction is needed, requiring hundreds of projections, making this procedure not suitable for real-time inspection. In contrast to CT-based inspection, radiograph-based inspection only requires a few radiographs that then can be compared with simulated projections from the reference CAD model. For an effective comparison, however, an accurate 3D pose estimation of the object and consequent alignment between the measured object and the reference model are crucial. In this paper, we present an inline projection-based 3D pose estimation framework using convolutional neural networks (CNNs). Through realistic simulation experiments, we show that, with only two projections, estimation of the pose of the object is possible at the resolution of the acquisition system.},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2159,
	title = {Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	abstract = {In multi-slice super-resolution reconstruction (MS-SRR), a high resolution image, referred to as SRR image, is estimated from a series of multi-slice images with a low through-plane resolution. This work proposes a framework based on the Bayesian mean squared error of the Maximum A Posteriori estimator of a SRR image to compare the accuracy and precision of two commonly adopted MR acquisition strategies in MS-SRR. The first strategy consists in acquiring a set of multi-slice
images, where each image is shifted in the through-plane direction by a different, sub-pixel distance. The latter consists in acquiring a set of multi-slice images, where each image is rotated around the frequency or phase-encoding axis by a different rotation angle. Results show that MS-SRR based on rotated multi-slice images outperforms MS-SRR based on shifted multi-slice images in terms of accuracy, precision and mean squared error of the reconstructed image.},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {2099,
	title = {Dark field sensitivity in single mask edge illumination lung imaging},
	booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
	year = {2021},
	pages = {775-778},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Nice, France},
	doi = {10.1109/ISBI48211.2021.9434024},
	url = {https://ieeexplore.ieee.org/document/9434024},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2180,
	title = {Decoding Multiple Sclerosis EDSS disability scores from MRI using Deep Learning},
	volume = {34},
	year = {2021},
	pages = {S57-S58},
	doi = {10.1007/s10334-021-00947-8},
	author = {Roberto Paolella and Ezequiel de la Rosa and Diana M. Sima and Dominique Dive and Francoise Durand-Dubief and Dominique Sappey-Marinier and Ben Jeurissen and Jan Sijbers and Thibo Billiet}
}
@inproceedings {2158,
	title = {A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	author = {Luis Filipe Alves Pereira and Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@article {2171,
	title = {Dynamic few-view X-ray imaging for inspection of CAD-based objects},
	journal = {Expert Systems with Applications},
	volume = {180},
	year = {2021},
	pages = {115012},
	keywords = {CAD, Dynamic acquisition, Few-view inspection, Pose estimation, Visibility angles},
	issn = {0957-4174},
	doi = {https://doi.org/10.1016/j.eswa.2021.115012},
	url = {https://www.sciencedirect.com/science/article/pii/S095741742100453X},
	author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer}
}
@article {2137,
	title = {Evaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline{\textquoteright}s scale layer thickness},
	journal = {Alexandria Engineering Journal},
	volume = {60},
	year = {2021},
	abstract = {The main objective of the present research is to combine the effect of scale thickness on the flow pattern and characteristics of two-phase flow that is used in oil industry. In this regard, an intelligent nondestructive technique based on combination of gamma radiation attenuation and artificial intelligence is proposed to determine the type of flow pattern and gas volume percentage in two phase flow independent of petroleum pipeline{\textquoteright}s scale layer thickness. The proposed system includes a dual energy gamma source, composed of Barium-133 and Cesium-137 radioisotopes, and two sodium iodide detectors for recording the transmitted and scattered photons. Support Vector Machine was implemented for regime identification and Multi-Layer Perceptron with Levenberg Marquardt algorithm was utilized for void fraction prediction. Total count in the scattering detector and counts under photo peaks of Barium-133 and Cesium-137 were assigned as the inputs of networks. The results show the ability of presented system to identify the annular regime and measure the void fraction independent of petroleum pipeline{\textquoteright}s scale layer thickness.},
	author = {Mohammadmehdi Roshani and Giang T.T. Phan and Gholam Hossein Roshani and Robert Hanus and Trung Duong and Enrico Corniani and Ehsan Nazemi and ElMostafa Kalmouni}
}
@article {2188,
	title = {Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique},
	journal = {Physics in Medicine and Biology},
	volume = {66},
	year = {2021},
	chapter = {165008},
	doi = {10.1088/1361-6560/ac16bc},
	author = {Joaquim Sanctorum and Sam Van Wassenbergh and Van Nguyen and Jan De Beenhouwer and Jan Sijbers and Joris J. J. Dirckx}
}
@article {2092,
	title = {FleXCT: a Flexible X-ray CT scanner with 10 degrees of freedom},
	journal = {Optics Express},
	volume = {29},
	year = {2021},
	pages = {3438-3457},
	doi = {https://doi.org/10.1364/OE.409982},
	author = {Bjorn De Samber and Jens Renders and Tim Elberfeld and Yves Maris and Jonathan Sanctorum and Nathana{\"e}l Six and Liang, Zhihua and Jan De Beenhouwer and Jan Sijbers}
}
@article {2142,
	title = {Fracture patterns in midshaft clavicle fractures},
	journal = {Acta Orthop Belg },
	volume = {87},
	year = {2021},
	pages = {501-507},
	doi = {https://doi.org/10.52628/87.3.16},
	author = {Van Tongel, Alexander and Lieven De Wilde and Yasunori Shimamura and Jan Sijbers and Toon Huysmans}
}
@article {2203,
	title = {Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images},
	journal = {IEEE Transactions on Computational Imaging},
	volume = {7},
	year = {2021},
	pages = {1304-1313},
	doi = {10.1109/TCI.2021.3133226},
	author = {Nathana{\"e}l Six and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2179,
	title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge},
	journal = {NeuroImage},
	volume = {240},
	year = {2021},
	doi = {https://doi.org/10.1016/j.neuroimage.2021.118367},
	author = {Alberto De Luca and Andrada Ianus and Alexander Leemans and Marco Palombo and Noam Shemesh and Hui Zhang and Daniel C Alexander and Markus Nilsson and Martijn Froeling and Geert-Jan Biessels and Mauro Zucchelli and Matteo Frigo and Enes Albay and Sara Sedlar and Abib Alimi and Samuel Deslauriers-Gauthier and Rachid Deriche and Rutger Fick and Maryam Afzali and Tomasz Pieciak and Fabian Bogusz and Santiago Aja-Fernandez and Evren Ozarslan and Derek K. Jones and Haoze Chen and Mingwu Jin and Zhijie Zhang and Fenxiang Wang and Vishwesh Nath and Prasanna Parvathaneni and Jan Morez and Jan Sijbers and Ben Jeurissen and Shreyas and Fadnavis and Stefan Endres and Ariel Rokem and Eleftherios Garyfallidis and Irina Sanchez and Vesna Prchkovska and Paulo Rodrigues and Bennet A. Landman and Kurt G Schilling}
}
@article {2148,
	title = {Geometry Calibration of a Modular Stereo Cone-Beam X-ray CT System},
	journal = {Journal of Imaging},
	volume = {7},
	year = {2021},
	pages = {1-12},
	doi = {https://doi.org/10.3390/jimaging7030054},
	author = {Van Nguyen and Joaquim Sanctorum and Sam Van Wassenbergh and Joris J. J. Dirckx and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2205,
	title = {High-resolution T2* mapping of the knee based on UTE Spiral VIBE MRI},
	volume = {34},
	year = {2021},
	pages = {S53-S54},
	author = {Celine Smekens and Quinten Beirinckx and Floris Vanhevel and Pieter Van Dyck and Arnold Jan den Dekker and Jan Sijbers and Thomas Janssens and Ben Jeurissen}
}
@mastersthesis {2140,
	title = {The impact of long-duration spaceflight on brain structure and function},
	volume = {Doctor of Science},
	year = {2021},
	school = {University of Antwerp},
	type = {PhD thesis},
	abstract = {In over half a century of crewed missions to space, many different effects of spaceflight on the human body have been uncovered so far. However, little focus has been directed to investigating how space stressors affect the human brain. The largest body of work in this dissertation describes pioneering findings on brain structural and functional changes after spaceflight in Roscosmos cosmonauts by means of multi-modal magnetic resonance imaging (MRI) in a longitudinal and prospective design. Structural MRI modalities, such as T1-weighted and diffusion MRI, were used to unravel macroscopic volume and microstructural brain tissue composition changes. We found a widespread redistribution of the cerebrospinal fluid (CSF) with secondary mechanistic effects on the grey matter (GM) tissue. We also revealed increased neural tissue volume in motor regions of the brain that suggest evidence for structural brain adaptations, also known as neuroplasticity, associated with altered motor strategies in space. Most CSF changes after spaceflight were still detectable more than half a year after return to Earth, while the GM changes after spaceflight partially reversed in the long term. In addition, functional MRI data was acquired in these cosmonauts to study functional reorganisation of the brain after spaceflight, showing numerous functional connectivity (FC) alterations after spaceflight. Some of these changes persisted in the longer-term, whereas other changes returned back to pre-flight levels. Furthermore, this work also describes the experimental work and preliminary analyses of several Earth-based models. One is a longitudinal MRI pilot study in hindlimb-unloaded (HLU) mice, inducing fluid shifts to the head region, in order to better understand the consequence of these fluid shifts on the brain. A second study was performed in fighter pilots as a model for exposure to high g-levels and sensory conflicts, in which FC was compared to that in a control group. This work rendered a vast increase in available information on structural and functional brain changes after spaceflight compared to several years ago. In the future, the underlying mechanisms of the observed findings need to be understood in more detail. Ultimately, we aim to characterise the effects space stressors have on the brain, to then attempt to mitigate these changes through countermeasures and characterise beneficial coping mechanisms that we can enhance, in order to be fully prepared for future exploration missions into deep space.},
	author = {Steven Jillings}
}
@article {2096,
	title = {Joint Deblurring and Denoising of THz Time-Domain Images},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	pages = {162-176},
	doi = {10.1109/ACCESS.2020.3045605},
	author = {Marina Ljubenovi{\'c} and Lina Zhuang and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2198,
	title = {Mesh-based reconstruction of dynamic foam images using X-ray CT},
	booktitle = {International Conference on 3D Vision (3DV2021)},
	year = {2021},
	pages = {1312-1320},
	doi = {10.1109/3DV53792.2021.00138},
	author = {Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2163,
	title = {Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction},
	journal = {Applied Sciences},
	volume = {11},
	year = {2021},
	chapter = {3145},
	doi = {https://doi.org/10.3390/app11073145},
	author = {Ehsan Nazemi and Nathana{\"e}l Six and Domenico Iuso and Bjorn De Samber and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2178,
	title = {Motion compensating X-ray micro-CT of diamonds in a processing stage},
	year = {2021},
	month = {September},
	author = {Jens Renders and Anh-Tuan Nguyen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2189,
	title = {Multi-contrast multi-shot EPI for accelerated diffusion MRI},
	booktitle = {43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
	year = {2021},
	pages = {3869-3872},
	doi = {10.1109/EMBC46164.2021.9630069},
	author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {2182,
	title = {Optimal experimental design for the T2-weighted diffusion kurtosis imaging free water elimination model},
	volume = {34},
	year = {2021},
	pages = {S54-S55},
	doi = {https://doi.org/10.1007/s10334-021-00947-8},
	author = {Vincenzo Anania and Ben Jeurissen and Jan Morez and Annemieke Eline Buikema and Thibo Billiet and Jan Sijbers and Arnold Jan den Dekker}
}
@conference {2174,
	title = {Outcome prediction in Mild Traumatic Brain Injury patients using conventional and diffusion MRI via Support Vector Machine: A CENTER-TBI study},
	year = {2021},
	author = {Maira Siqueira Pinto and Stefan Winzeck and Marta M. Correia and Evgenios N. Kornaropoulos and David K. Menon and Ben Glocker and Arnold Jan den Dekker and Jan Sijbers and Pieter-Jan Guns and Pieter Van Dyck and Virginia F. J. Newcombe}
}
@conference {2185,
	title = {Outcome prediction of mild traumatic brain injury using support vector machine based on longitudinal MRdiffusion imaging from CENTER-TBI},
	volume = {34},
	year = {2021},
	pages = {S54},
	doi = {10.1007/s10334-021-00947-8},
	author = {Maira Siqueira Pinto and Stefan Winzeck and S. Richter and Marta M. Correia and Evgenios N. Kornaropoulos and David K. Menon and Ben Glocker and Pieter-Jan Guns and Arnold Jan den Dekker and Jan Sijbers and Virginia F. J. Newcombe and Pieter Van Dyck}
}
@article {2071,
	title = {Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography},
	journal = {Measurement Science and Technology},
	volume = {32},
	year = {2021},
	pages = {1-11},
	doi = {10.1088/1361-6501/abb33e},
	author = {Joaquim Sanctorum and Sam Van Wassenbergh and Van Nguyen and Jan De Beenhouwer and Jan Sijbers and Joris J. J. Dirckx}
}
@inproceedings {2169,
	title = {Recurrent Inference Machines as Inverse Problem Solvers for MR Relaxometry},
	booktitle = { MIDL 2021 - Medical Imaging with Deep Learning},
	year = {2021},
	author = {Emanoel Ribeiro Sabidussi and Matthan Caan and Shabab Bazrafkan and Arnold Jan den Dekker and Jan Sijbers and Wiro J Niessen and Dirk H J Poot}
}
@article {2190,
	title = {Recurrent Inference Machines as inverse problem solvers for MR relaxometry},
	journal = {Medical Image Analysis},
	volume = {74},
	year = {2021},
	pages = {1-11},
	doi = {https://doi.org/10.1016/j.media.2021.102220},
	author = {Emanoel Ribeiro Sabidussi and Stefan Klein and Matthan Caan and Shabab Bazrafkan and Arnold Jan den Dekker and Jan Sijbers and Wiro J Niessen and Dirk H J Poot}
}
@conference {2181,
	title = {Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer},
	volume = {34},
	year = {2021},
	pages = {S56-S57},
	doi = {10.1007/s10334-021-00947-8},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {2100,
	title = {Statistical shape and pose model of the forearm for custom splint design},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2021},
	pages = {1669-1672},
	doi = {10.1109/ISBI48211.2021.9434067},
	author = {Femke Danckaers and Jeroen Van Houtte and Brian G Booth and Frederik Verstreken and Jan Sijbers}
}
@inproceedings {2187,
	title = {A study of terahertz beam simulation with ray tracing for computed tomography},
	booktitle = {2021 OSA Imaging and Applied Optics Congress},
	year = {2021},
	doi = {10.1364/AIS.2021.JTu5A.37},
	author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2160,
	title = {Super-resolution T2* mapping of the knee using UTE Spiral VIBE MRI},
	year = {2021},
	pages = {3920},
	abstract = {T2* mapping using ultrashort echo time (UTE) MRI allows for quantitative evaluation of collagen-rich knee structures with short mean transverse relaxation times. However, acquisitions with low through-plane resolution are commonly used to obtain T2* maps within reasonable scan times, affecting the accuracy of the estimations because of partial volume effects. In this work, model-based super-resolution reconstructions based on UTE Spiral VIBE MRI were performed to obtain high-resolution T2* maps of knee structures within a reasonable scan time. The obtained T2* maps are comparable to maps generated with direct 3D UTE Spiral VIBE acquisitions while requiring approximately 25\% less scan time.},
	author = {Celine Smekens and Quinten Beirinckx and Floris Vanhevel and Pieter Van Dyck and Arnold Jan den Dekker and Jan Sijbers and Thomas Janssens and Ben Jeurissen}
}
@inproceedings {2157,
	title = {Tabu-DART: a dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	author = {Daniel Frenkel and Jan De Beenhouwer and Jan Sijbers}
}
@article {2087,
	title = {To Recurse or not to Recurse A Low Dose CT Study},
	journal = {Progress in Artificial Intelligence},
	volume = {10},
	year = {2021},
	pages = {65{\textendash}81},
	doi = {https://doi.org/10.1007/s13748-020-00224-0},
	author = {Shabab Bazrafkan and Vincent Van Nieuwenhove and Joris Soons and Jan De Beenhouwer and Jan Sijbers}
}
@conference {2081,
	title = {3D Atomic Scale Quantification of Nanostructures and their Dynamics Using Model-based STEM},
	year = {2020},
	author = {Sandra Van Aert and Annick De Backer and De wael, A and Jarmo Fatermans and Friedrich, T and Ivan Lobato and O{\textquoteright}Leary, C M. and Varambhia, A and Thomas Altantzis and Jones, L and Arnold Jan den Dekker and Peter D Nellist and Sara Bals}
}
@mastersthesis {2069,
	title = {Accurate and precise perfusion parameter estimation in pseudo-continuous arterial spin labeling MRI},
	volume = {PhD in Sciences/Physics},
	year = {2020},
	type = {PhD thesis},
	author = {Piet Bladt}
}
@inproceedings {2053,
	title = {Accurate terahertz simulation with ray tracing incorporating beam shape and refraction},
	booktitle = {IEEE ICIP },
	year = {2020},
	pages = {3035-3039},
	doi = {10.1109/ICIP40778.2020.9190937},
	author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1979,
	title = {An adaptive probability map for the Discrete Algebraic Reconstruction Technique},
	booktitle = {10th Conference on Industrial Computed Tomography (ICT 2020)},
	year = {2020},
	pages = {1-6},
	author = {Daniel Frenkel and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2028,
	title = {Adjoint pairs of image warping operators for motion modeling in 4D-CT},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	author = {Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2057,
	title = {Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibres},
	journal = {Nondestructive Testing and Evaluation},
	volume = {35},
	year = {2020},
	pages = {328-341},
	doi = {https://doi.org/10.1080/10589759.2020.1774583},
	author = {Bernhard Fr{\"o}hler and Tim Elberfeld and Torsten M{\"o}ller and Hans-Christian Hege and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2084,
	title = {Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020)},
	year = {2020},
	author = {Benjamin Auer and Kesava Kalluri and Aly H. Abayazeed and Jan De Beenhouwer and Navid Zeraatkar and Clifford Lindsay and Neil Momsen and R. Garrett Richards and Micaehla May and Matthew A. Kupinski and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@article {2063,
	title = {Atom column detection from simultaneously acquired ABF and ADF STEM images},
	journal = {Ultramicroscopy},
	volume = {219},
	year = {2020},
	pages = {113046},
	doi = {https://doi.org/10.1016/j.ultramic.2020.113046},
	author = {Fatermans, J. and Arnold Jan den Dekker and M{\"u}ller-Caspary, K. and N Gauquelin and Jo Verbeeck and Sandra Van Aert}
}
@conference {2091,
	title = {Bayesian model selection for atom column detection from ABF-ADF STEM images},
	year = {2020},
	author = {Fatermans, J. and Arnold Jan den Dekker and N Gauquelin and Jo Verbeeck and Sandra Van Aert}
}
@inproceedings {2027,
	title = {BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	pages = {518-521},
	author = {Van Nguyen and Jan De Beenhouwer and Shabab Bazrafkan and A-T. Hoang and Sam Van Wassenbergh and Jan Sijbers}
}
@inproceedings {2034,
	title = {CNN-based Deblurring of Terahertz Images},
	booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)},
	volume = {4},
	year = {2020},
	pages = {323-330},
	doi = {10.5220/0008973103230330},
	author = {Marina Ljubenovi{\'c} and Shabab Bazrafkan and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1951,
	title = {A Comparative Study Between Three Measurement Methods to Predict 3D Body Dimensions Using Shape Modelling},
	booktitle = {Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping},
	volume = {975},
	year = {2020},
	pages = {464{\textendash}470},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {In times of online shopping, it is a challenge to select the right size of the desired clothing without fitting it before ordering. Therefore, this study describes three techniques to predict 3D upper body dimensions. The first method used basic personal parameters (gender, age, weight and length), the second technique used also the shoulder width and the last method used a 3D Styku scan to add extra input parameters. The accuracy of the three prediction methods was compared against hand measurements for 17 upper body dimensions of 37 subjects. The Intraclass Correlation Coefficient increases with 11.2\% for the Styku method compared to the other methods. For chest, hip and waist measurements, the basic method is reliable to predict 3D body dimensions and indicate the right size from an existing collection. For more accurate upper body dimensions as needed for producing custom made clothing, a 3D Styku scan can supply the desired input.},
	isbn = {978-3-030-20216-3},
	doi = {10.1007/978-3-030-20216-3_43},
	author = {Peeters, Thomas and Vleugels, Jochen and Stijn Verwulgen and Femke Danckaers and Toon Huysmans and Jan Sijbers and De Bruyne, Guido},
	editor = {Di Nicolantonio, Massimo and Rossi, Emilio and Alexander, Thomas}
}
@article {1956,
	title = {The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling},
	journal = {NMR in Biomedicine},
	volume = {33},
	year = {2020},
	pages = {1-17},
	doi = {https://doi.org/10.1002/nbm.4182},
	author = {Piet Bladt and Arnold Jan den Dekker and Clement, Patricia and Eric Achten and Jan Sijbers}
}
@inproceedings {1977,
	title = {Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT},
	booktitle = {10th Conference on Industrial Computed Tomography (ICT 2020)},
	year = {2020},
	author = {Alice Presenti and Shabab Bazrafkan and Jan Sijbers and Jan De Beenhouwer}
}
@article {2064,
	title = {Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study},
	journal = {European Radiology},
	volume = {34},
	year = {2020},
	pages = {6673{\textendash}6684},
	doi = {10.1007/s00330-020-07051-w},
	author = {Pieter Van Dyck and Thibo Billiet and Damien Desbuquoit and Peter Verdonk and Christiaan H. Heusdens and Ella Roelant and Jan Sijbers and Martijn Froeling}
}
@article {2011,
	title = {The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model},
	journal = {Computers in Biology and Medicine},
	volume = {117},
	year = {2020},
	pages = {1-13},
	doi = {https://doi.org/10.1016/j.compbiomed.2020.103600},
	author = {Keustermans, William and Toon Huysmans and Bert Schmelzer and Jan Sijbers and Joris J. J. Dirckx}
}
@article {2016,
	title = {Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)},
	journal = {Analytica Chimica Acta},
	volume = {1106},
	year = {2020},
	pages = {22-32},
	abstract = {Analytical capabilities of Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS) and Synchrotron Radiation based X-ray Fluorescence (SR nano-XRF) techniques were compared for nanochemical imaging of polymorphonuclear human neutrophils (PMNs). PMNs were high pressure frozen (HPF), cryosubstituted, embedded in Spurr{\textquoteright}s resin and cut in thin sections (500 nm and 2 mm for both techniques resp.) Nano-SIMS enabled nanoscale mapping of isotopes of C, N, O, P and S, while SR based nano-XRF enabled trace level imaging of metals like Ca, Mn, Fe, Ni, Cu and Zn at a resolution of approx. 50 nm.

The obtained elemental distributions were compared with those of whole, cryofrozen PMNs measured at the newly developed ID16A nano-imaging beamline at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France. Similarities were observed for elements more tightly bound to the cell structure such as phosphorus and sulphur, while differences for mobile ions such as chlorine and potassium were more pronounced. Due to the observed elemental redistribution of mobile ions such as potassium and chlorine, elemental analysis of high pressure frozen (HPF), cryo-substituted and imbedded cells should be interpreted critically. Although decreasing analytical sensitivity occurs due to the presence of ice, analysis of cryofrozen cells - close to their native state - remains the golden standard. In general, we found nanoscale secondary ion mass spectrometry (nano-SIMS) and synchrotron radiation based nanoscopic X-ray fluorescence (SR nano-XRF) to be two supplementary alternatives for nanochemical imaging of single cells at the nanoscale.},
	doi = {10.1016/j.aca.2020.01.054},
	author = {Bjorn De Samber and Riet De Rycke and Michiel De Bruyne and Michiel Kienhuis and Linda Sandblad and Sylvain Bohic and Peter Cloetens and Constantin Urban and Lubos Polerecky and Laszlo Vincze}
}
@inproceedings {2072,
	title = {Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks},
	booktitle = {ICTAI 2020},
	year = {2020},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Johann Kastner and Jan Sijbers}
}
@article {2037,
	title = {Harmonisation of Brain Diffusion MRI: Concepts and Methods},
	journal = {Frontiers in Neuroscience },
	volume = {14},
	year = {2020},
	month = {03/2020},
	pages = {1-17},
	doi = {https://doi.org/10.3389/fnins.2020.00396},
	author = {Maira Siqueira Pinto and Roberto Paolella and Thibo Billiet and Pieter Van Dyck and Pieter-Jan Guns and Ben Jeurissen and Annemie Ribbens and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {2021,
	title = {Improved voxel-wise quantification of diffusion and kurtosis metrics in the presence of noise and intensity outliers},
	year = {2020},
	url = {https://www.ismrm-benelux.org/wp-content/uploads/2020/01/Proceedings2020.pdf},
	author = {Vincenzo Anania and Thibo Billiet and Ben Jeurissen and Annemie Ribbens and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {2024,
	title = {Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept},
	volume = {28},
	year = {2020},
	abstract = {To address the issue of phase induced artifacts in multi-shot diffusion weighted imaging, we propose a model-based framework which enables the joint estimation of diffusion and phase parameters
directly from the multi-shot k-q-space. In a simulation study, we show that using this framework, diffusion parameters can be estimated more accurately and precisely than with the conventional
method (image reconstruction followed by voxel-wise model fitting) that ignores phase differences.},
	keywords = {Diffusion MRI, MRI, Phase estimation},
	author = {Banafshe Shafieizargar and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {2025,
	title = {Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept},
	volume = {12},
	year = {2020},
	abstract = {To address the issue of phase induced artifacts in multi-shot diffusion weighted imaging, we propose a model-based framework which enables the joint estimation of diffusion and phase parameters
directly from the multi-shot k-q-space. In a simulation study, we show that using this framework, diffusion parameters can be estimated more accurately and precisely than with the conventional
method (image reconstruction followed by voxel-wise model fitting) that ignores phase differences.},
	keywords = {Diffusion MRI, MRI, Phase estimation},
	author = {Banafshe Shafieizargar and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1971,
	title = {Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study},
	journal = {Fundamenta Informaticae},
	volume = {172},
	year = {2020},
	pages = {105{\textendash}128},
	abstract = {Magnetic resonance imaging (MRI) based T1 mapping allows spatially resolved quantification of the tissue-dependent spin-lattice relaxation time constant T1, which is a potential biomarker of various neurodegenerative diseases, including Multiple Sclerosis, Alzheimer disease, and Parkinson{\textquoteright}s disease. In conventional T1 MR relaxometry, a quantitative T1 map is obtained from a series of T1-weighted MR images. Acquiring such a series, however, is time consuming. This has sparked the development of more efficient T1 mapping methods, one of which is a super-resolution reconstruction (SRR) framework in which a set of low resolution (LR) T1-weighted images is acquired and from which a high resolution (HR) T1 map is directly estimated. In this paper, the SRR T1 mapping framework is augmented with motion estimation. That is, motion between the acquisition of the LR T1-weighted images is modeled and the motion parameters are estimated simultaneously with the T1 parameters. Based on Monte Carlo simulation experiments, we show that such an integrated motion/relaxometry estimation approach yields more accurate T1 maps compared to a previously reported SRR based T1 mapping approach.},
	doi = {10.3233/FI-2020-1896},
	author = {Quinten Beirinckx and Gabriel Ramos-Llord{\'e}n and Ben Jeurissen and Dirk H J Poot and Paul M Parizel and Marleen Verhoye and Jan Sijbers and Arnold Jan den Dekker}
}
@article {2083,
	title = {Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging},
	journal = {Journal of Nuclear Medicine},
	volume = {61},
	year = {2020},
	pages = {573},
	abstract = {573Objectives: Given its excellent resolution versus sensitivity trade-off, multi-pinhole SPECT has become a powerful tool for clinical imaging of small human structures such as the brain [1]. Our research team is designing and constructing a next-generation multi-pinhole system, AdaptiSPECT-C, for quantitative brain imaging. In this context, keel-edge pinhole has proven to increase significantly attenuation of gamma rays through the edges of the pinhole aperture compared to the most commonly clinically used knife-edge profile [2-4]. In this work, we investigate the potential improvement in imaging performance of multiple keel-edge pinhole profiles as a function of keel height for AdaptiSPECT-C compared to a knife-edge collimation for 123I-IMP brain perfusion. Methods: The prototype AdaptiSPECT-C system used herein is composed of 23 hexagonal detector modules hemi-spherically arranged along 3 rings. For modeling in GATE simulation (GS) [5], each of these modules is composed of 1.5 mm radius pinhole and a 1 cm thick NaI(Tl) crystal with a 5 cm thick back-scattering compartment, which was considered to simulate 123I down-scatter interactions. Multiple keel-edge heights, corresponding to 0.0 (knife edge), 0.375, 0.75, 1.0, 1.125, 1.5, 1.875, and 2.25 mm were studied. We evaluated the volumetric sensitivity and relative amount of collimator penetration for a 15\% energy window centered at 159 keV in simulated projections of a 21 cm diameter spherical source (e.g. corresponding to the system{\textquoteright}s volume of interest) centered at the focal point of the pinholes. For reconstruction, an approach developed in our group was employed for modeling using GS the system response and especially collimator penetration into the system matrix [6,7] for the knife and the keel-edge designs. An XCAT [8] brain phantom with source distribution for the perfusion imaging agent 123I-IMP was simulated using the pinhole designs. Projection were acquired considering two scenarios: noise free (S1), and equal imaging time comparison for a realistic clinical scan time (e.g. 30 min [9,10]) (S2). Reconstructions were performed with a customized 3D-MLEM software into images of 1203 voxels of (2 mm)3. The reconstructed images were then compared to the ground truth image in terms of the normalized root mean squared error (NRMSE) and activity recovery (\%AR) for selected three-dimensional brain regions. Results: A keel-edge height of 0.375-0.75 mm represents the best choice leading to a significant reduction of the amount of penetration (up to  50\%) at the expense of sensitivity (-20\%) compared to a knife-edge profile. Visually, for all scenarios, the use of such a keel-edge profile leads to better separation of the brain structures, especially the caudate and the putamen. When sensitivity is not taken into account (e.g. noise free scenario), increasing the keel height improves NRMSE results. For an equal imaging time comparison, lowest NRMSE values are achieved for a 0.375-0.75 mm keel-height. A further keel-height increase degrades the NRMSE results due to significant loss of counts compared to knife-edge design. A 0.75 mm keel height leads on average to the best \%ARs (e.g. closest value to 100\%), especially for the striatum and putamen. For cortex and cerebellum regions, \%ARs are comparable with those obtained for a knife-edge design. Conclusion: In this work, we demonstrated that the use of a  0.75 mm height keel-edge profile for AdaptiSPECT-C incorporating 1.5 mm radius pinholes leads to superior imaging performance compared to knife-edge collimation for clinical 123I brain perfusion imaging. A range of aperture radii from 0.5 to 3.5 mm for each design have been investigated and will be shown at the time of the conference. We are currently working on performing a numerical-observer task-performance study of defect-detection in perfusion. Research Support: National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health, Grant No R01 EB022521. Volumetric Sensitivities, Amount of Penetration, and Lowest NRMSE for the designs investigated},
	url = {http://jnm.snmjournals.org/content/61/supplement_1/573.abstract},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Navid Zeraatkar and Neil Momsen and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@article {2055,
	title = {A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system},
	journal = {Nondestructive Testing and Evaluation },
	volume = {35},
	year = {2020},
	pages = { 252-265},
	doi = {https://doi.org/10.1080/10589759.2020.1774580},
	author = {Van Nguyen and Jan De Beenhouwer and Joaquim Sanctorum and Sam Van Wassenbergh and Shabab Bazrafkan and Joris J. J. Dirckx and Jan Sijbers}
}
@article {2010,
	title = {A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants},
	journal = {Scientific Reports},
	volume = {10},
	year = {2020},
	doi = {https://doi.org/10.1038/s41598-019-57405-8},
	author = {Brian G. Booth and Jan Sijbers and Jan De Beenhouwer}
}
@article {2074,
	title = {Macro- and microstructural changes in cosmonauts{\textquoteright} brains after long-duration spaceflight},
	journal = {Science Advances},
	volume = {6},
	year = {2020},
	month = {Apr-09-2020},
	pages = {eaaz9488},
	abstract = {Long-duration spaceflight causes widespread physiological changes, although its effect on brain structure remains poorly understood. In this work, we acquired diffusion magnetic resonance imaging to investigate alterations of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) compositions in each voxel, before, shortly after, and 7 months after long-duration spaceflight. We found increased WM in the cerebellum after spaceflight, providing the first clear evidence of sensorimotor neuroplasticity. At the region of interest level, this increase persisted 7 months after return to Earth. We also observe a widespread redistribution of CSF, with concomitant changes in the voxel fractions of adjacent GM. We show that these GM changes are the result of morphological changes rather than net tissue loss, which remained unclear from previous studies. Our study provides evidence of spaceflight-induced neuroplasticity to adapt motor strategies in space and evidence of fluid shift{\textendash}induced mechanical changes in the brain.},
	doi = {10.1126/sciadv.aaz9488},
	url = {https://advances.sciencemag.org/content/6/36/eaaz9488},
	author = {Steven Jillings and Angelique Van Ombergen and Tomilovskaya, Elena and Rumshiskaya, Alena and Litvinova, Liudmila and Nosikova, Inna and Pechenkova, Ekaterina and Rukavishnikov, Ilya and Kozlovskaya, Inessa B. and Manko, Olga and Danilichev, Sergey and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Petrovichev, Victor and Laureys, Steven and zu Eulenburg, Peter and Jan Sijbers and Floris L Wuyts and Ben Jeurissen}
}
@inproceedings {2133,
	title = {Newton-Krylov Methods For Polychromatic X-Ray CT},
	booktitle = {2020 IEEE International Conference on Image Processing (ICIP)},
	year = {2020},
	pages = {3045-3049},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Abu Dhabi},
	keywords = {Attenuation, computed tomography, image reconstruction, Jacobian matrices, Linear programming, Mathematical model, Structural beams},
	isbn = {978-1-7281-6396-3},
	doi = {10.1109/ICIP40778.2020.9190717},
	url = {https://ieeexplore.ieee.org/abstract/document/9190717},
	author = {Nathana{\"e}l Six and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2018,
	title = {Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning},
	journal = {Food Control},
	volume = {113},
	year = {2020},
	pages = {1-13},
	doi = {https://doi.org/10.1016/j.foodcont.2020.107170},
	author = {Tim Van De Looverbosch and Hafizur Rahman Bhuiyan and Pieter Verboven and Manuel Dierick and Van Loo, D. and Jan De Beenhouwer and Jan Sijbers and Bart Nicolai}
}
@conference {2019,
	title = {Optimal design of a T1 super-resolution reconstruction experiment: a simulation study},
	year = {2020},
	author = {Michele Nicastro and Quinten Beirinckx and Piet Bladt and Ben Jeurissen and Stefan Klein and Jan Sijbers and Dirk H J Poot and Arnold Jan den Dekker}
}
@inproceedings {2052,
	title = {Projection angle adapted distortion correction in high-speed image-intensifier based tomography},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	author = {Joaquim Sanctorum and Van Nguyen and Jan Sijbers and Sam Van Wassenbergh and Joris J. J. Dirckx}
}
@inproceedings {2054,
	title = {The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape},
	booktitle = {IEEE ICIP},
	year = {2020},
	pages = {3040-3044},
	doi = {10.1109/ICIP40778.2020.9191175},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@article {2082,
	title = {Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT},
	journal = {Journal of Nuclear Medicine},
	volume = {61},
	year = {2020},
	pages = {103},
	abstract = {103Objectives: Brain SPECT has many clinical applications, especially for cerebral blood flow and dopamine transporter imaging [1,2]. In this context, a dedicated brain imaging, multi-pinhole system, AdaptiSPECT-C, is being developed by our group. Recent studies in cardiac and small animal imaging have demonstrated that the use of curved detector could improve image quality, by reducing parallax errors due to the depth of interaction (DOI) effect [3,4]. In this simulation study, we proposed to investigate using reconstruction with DOI modeling the potential advantage in imaging performance of curved over flat detectors for 123I-IMP perfusion imaging using the AdaptiSPECT-C system. Methods: The AdaptiSPECT-C design used in this work consists of 26 detector modules, 158 by 158 mm2 in size, arranged around the patient{\textquoteright}s head in three rings. The simulated detector modules were composed of a 8 mm thick NaI(Tl) crystal coupled to a 5 cm thick back-scattering compartment, representing components behind the crystal, to model 123I down-scatter interactions. Each detector module is associated with a 1.36 mm radius direct knife-edge pinhole aperture collimator. Two different system designs were considered, one based on curved detectors, and the other on flat detectors. The curved detectors were designed so that the radius of curvature corresponds to the detector to system center distance (e.g. 30.5 cm). This distance was the same for the flat detectors. GATE simulation [5] was employed to compute the system matrix [6,7] for both detector designs by forming the system response for the activity within each three-dimensional image-voxel of a 24 cm diameter sphere, thus including DOI variations and corrections in reconstruction [6,7]. An XCAT brain phantom [8] emulating 123I-IMP perfusion source distribution was simulated using the two designs. Data were acquired following three scenarios: noise free case (S1), equal number of counts comparison (S2) (e.g. 5.5M detected counts [9]), and equal imaging time comparison for the typical scan time (e.g. 30 min [10]) (S3). For S3, the total number of counts for the curved and flat detector designs, were respectively 9.24M and 9.17M. Projections were reconstructed with 3D-MLEM into images of 1203 voxels of (2 mm)3 and reconstruction compared to the ground truth image. The normalized root mean squared error (NRMSE) as well as percentage of activity recovery (\%AR) for several brain regions were used to evaluate the image quality. Results: Only a small gain in volumetric sensitivity ( 0.8\%) was obtained with the curved detector design. Qualitatively, the reconstructions for the curved and flat detector designs appear similar for all the 3 noise scenarios. Differences are mostly for the peripheral regions of the head where the differences in the obliquity of the gamma-rays passing through the apertures would be the greatest. Due to lower activity, those regions are also more impacted by noise. Quantitatively, a slight NRMSE improvement using curved detectors was seen. The curved detector design leads on average to the best ARs, especially for the striatum and putamen. Regions at the edges of the brain (e.g. cortex and cerebellum), more impacted by DOI effect, are similarly recovered by the two designs. Conclusion: We demonstrated that using curved instead of flat detector for AdaptiSPECT-C with solely centered pinholes leads to small improvement in sensitivity and image quality based on visual inspection, NRMSE, and activity recovery analysis. Flat detector associated with a sophisticated DOI correction was found to lead to similar results than those obtained with the curved detector. Further investigation will be performed using additional pinholes irradiating the 4 quadrants of the detectors which will increase the obliquity of the rays striking the detectors and may thus result in larger difference. Research Support: Grant No R01 EB022521 (NIBIB).},
	url = {http://jnm.snmjournals.org/content/61/supplement_1/103.abstract},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Kimberly Doty and Navid Zeraatkar and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@inproceedings {2029,
	title = {Ring Artifact Reduction in Sinogram Space Using Deep Learning},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	author = {Maxime Nauwynck and Shabab Bazrafkan and Anneke Van Heteren and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2068,
	title = {Ringing Artefact Removal From Sparse View Tomosynthesis using Deep Neural Networks},
	booktitle = {The 6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	pages = {380-383},
	author = {Shabab Bazrafkan and Vincent Van Nieuwenhove and Joris Soons and Jan De Beenhouwer and Jan Sijbers}
}
@article {2070,
	title = {Small medial femoral condyle morphotype is associated with medial compartment degeneration and distinct morphological characteristics: a comparative pilot study},
	journal = {Knee Surgery, Sports Traumatology, Arthroscopy},
	year = {2020},
	doi = {https://doi.org/10.1007/s00167-020-06218-8},
	author = {Jonas Grammens and Annemieke Van Haver and Femke Danckaers and Brian G Booth and Jan Sijbers and Peter Verdonk}
}
@conference {2094,
	title = {Strategies for quantifying the 3D atomic structure and the dynamics of nanomaterials using model-based STEM},
	year = {2020},
	author = {Sandra Van Aert and Annick De Backer and De wael, A and Jarmo Fatermans and Arslan Irmak, E and Friedrich, T and Ivan Lobato and Jones, L and Arnold Jan den Dekker and Peter D Nellist and Sara Bals}
}
@article {2030,
	title = {Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis},
	journal = {Expert Systems With Applications},
	volume = {151},
	year = {2020},
	pages = {1-11},
	doi = {https://doi.org/10.1016/j.eswa.2020.113372},
	author = {Kristina Stankovi{\'c} and Toon Huysmans and Femke Danckaers and Jan Sijbers and Brian G Booth}
}
@article {2031,
	title = {Super-Resolution Magnetic Resonance Imaging of the Knee Using 2-Dimensional Turbo Spin Echo Imaging},
	journal = {Investigative Radiology},
	volume = {55},
	year = {2020},
	pages = {481-493},
	doi = {10.1097/RLI.0000000000000676},
	author = {Pieter Van Dyck and Celine Smekens and Floris Vanhevel and Eline De Smet and Ella Roelant and Jan Sijbers and Ben Jeurissen}
}
@conference {Bladt2020-mp,
	title = {Super-resolution reconstruction of single-PLD pseudo-continuous ASL images},
	year = {2020},
	pages = {3293},
	author = {Bladt, P and Beirinckx, Q and Van der Plas, M and Schmid, S and Teeuwisse, W and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers and van Osch, M}
}
@conference {2139,
	title = {Super-resolution reconstruction of single-PLD pseudo-continuous ASL images},
	year = {2020},
	pages = {3293},
	abstract = {Super-resolution reconstruction (SRR) allows for 3D high-resolution image reconstruction from a set of low-resolution multi-slice images with different orientations. Arterial spin labeling (ASL) is an interesting albeit complicated candidate for SRR, as it relies on subtraction. SRR-ASL can be performed on low-SNR subtracted or on low-contrast unsubtracted ASL data. Different ASL-SRR implementations were applied to single-PLD PCASL data and validated against traditional ASL-scans. Combining motion correction, super-resolution post-processing and pairwise subtraction of label-control pairs in a single framework yielded comparable CBF maps as with traditional HR-ASL. Furthermore, in certain slices, SRR-ASL appears to reconstruct the anatomical structure with higher fidelity.},
	author = {Piet Bladt and Quinten Beirinckx and Merlijn C E van der Plas and Sophie Schmid and Wouter M Teeuwisse and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers and M.J.P van Osch}
}
@conference {2015,
	title = {Super-resolution strategies for single-PLD pseudo-continuous ASL},
	year = {2020},
	address = {Arnhem, The Netherlands},
	abstract = {Super-resolution reconstruction (SRR) allows for 3D high-resolution image reconstruction from a set of low-resolution multi-slice images with different orientations. Arterial spin labeling (ASL) is an interesting albeit complicated candidate for SRR, as it relies on subtraction. SRR-ASL can be performed on low-SNR subtracted or on low-contrast unsubtracted ASL data. Different ASL-SRR implementations were applied to single-PLD PCASL data and validated against traditional ASL-scans. Combining motion correction, super-resolution post-processing and pairwise subtraction of label-control pairs in a single framework yielded comparable CBF maps as with traditional HR-ASL. Furthermore, in certain slices, SRR-ASL appears to reconstruct the anatomical structure with higher fidelity.},
	author = {Quinten Beirinckx and Piet Bladt and Merlijn C E van der Plas and Sophie Schmid and Wouter M Teeuwisse and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers and M.J.P van Osch}
}
@article {2051,
	title = {Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling},
	journal = {Magnetic Resonance in Medicine},
	volume = {84},
	year = {2020},
	pages = {2523-2536},
	doi = {10.1002/mrm.28314},
	author = {Piet Bladt and M.J.P van Osch and Clement, Patricia and Eric Achten and Jan Sijbers and Arnold Jan den Dekker}
}
@article {2077,
	title = {X-ray phase contrast simulation for grating-based interferometry using GATE},
	journal = {Optics Express},
	volume = {28},
	year = {2020},
	pages = {33390-33412},
	doi = {https://doi.org/10.1364/OE.392337},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1931,
	title = {A 3D Printed Thermal Manikin Head for Evaluating Helmets for Convective and Radiative Heat Loss},
	booktitle = {Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) Volume VII},
	volume = {VII},
	year = {2019},
	pages = {592{\textendash}602},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	abstract = {Thermal performance of three bicycle helmets for radiative and convective heat loss was evaluated through heat loss experiments in a wind tunnel. A 3D printed thermal manikin head of a 50th percentile western male population was developed. Thermal performance of a helmet was quantified by comparing the manikin head heat losses with and without helmet. Experiments were performed for two air velocities: 1.6 m/s and 6 m/s. An infrared heat lamp positioned above the manikin simulated the effect of solar load. The results from the experiments showed a convective cooling efficiency between 89{\%} and 96{\%} for open helmets and between 78{\%} and 83{\%} for closed helmets. The radiative heat gain ranged from 3.5 W to 4.5 W for open helmets and 5 W to 8 W for closed helmets.},
	keywords = {Convective heat loss, Heat transfer, Helmet thermal performance, Radiative heat gain, Thermal manikin head, Wind tunnel},
	isbn = {978-3-319-96070-8},
	doi = {10.1007/978-3-319-96071-5_63},
	author = {Shriram Mukunthan and Jochen Vleugels and Toon Huysmans and Mayor, Tiago Sotto and De Bruyne, Guido}
}
@inbook {1960,
	title = {Adaptable digital human models from 3D body scans},
	booktitle = {DHM and Posturography},
	volume = {VI},
	year = {2019},
	pages = {459-470},
	publisher = {Academic Press},
	organization = {Academic Press},
	chapter = {33},
	doi = {https://doi.org/10.1016/B978-0-12-816713-7.00033-7},
	author = {Femke Danckaers and Toon Huysmans and Jan Sijbers}
}
@article {2007,
	title = {Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform},
	journal = {Computers and Electronics in Agriculture},
	volume = {162},
	year = {2019},
	pages = {749-758},
	doi = {https://doi.org/10.1016/j.compag.2019.05.018},
	author = {Mohd Shahrimie Mohd Asaari and Stien Mertens and Stijn Dhondt and Dirk Inze and Nathalie Wuyts and Paul Scheunders}
}
@article {1955,
	title = {Aortic root sizing for transcatheter aortic valve implantation using a shape model parameterisation},
	journal = {Medical \& Biological Engineering \& Computing},
	volume = {57},
	year = {2019},
	month = {Jul},
	pages = {2081{\textendash}2092},
	abstract = {During a transcatheter aortic valve implantation, an axisymmetric implant is placed in an irregularly shaped aortic root. Implanting an incorrect size can cause complications such as leakage of blood alongside or through the implant. The aim of this study was to construct a method that determines the optimal size of the implant based on the three-dimensional shape of the aortic root. Based on the pre-interventional computed tomography scan of 89 patients, a statistical shape model of their aortic root was constructed. The weights associated with the principal components and the volume of calcification in the aortic valve were used as parameters in a classification algorithm. The classification algorithm was trained using the patients with no or mild leakage after their intervention. Subsequently, the algorithms were applied to the patients with moderate to severe leakage. Cross validation showed that a random forest classifier assigned the same size in 65 {\textpm} 7\% of the training cases, while 57 {\textpm} 8\% of the patients with moderate to severe leakage were assigned a different size. This initial study showed that this semi-automatic method has the potential to correctly assign an implant size. Further research is required to assess whether the different size implants would improve the outcome of those patients.},
	issn = {1741-0444},
	doi = {10.1007/s11517-019-01996-x},
	author = {Bosmans, Bart and Toon Huysmans and Lopes, Patricia and Verhoelst, Eva and Dezutter, Tim and de Jaegere, Peter and Jan Sijbers and Vander Sloten, Jos and Bosmans, Johan}
}
@inproceedings {1854,
	title = {An Articulating Statistical Shape Model of the Human Hand},
	booktitle = {Advances in Human Factors in Simulation and Modeling (AHFE 2018)},
	volume = {780},
	year = {2019},
	pages = {433{\textendash}445},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.},
	isbn = {978-3-319-94223-0},
	doi = {10.1007/978-3-319-94223-0_41},
	author = {Jeroen Van Houtte and Kristina Stankovi{\'c} and Brian G Booth and Femke Danckaers and Bertrand, V{\'e}ronique and Frederik Verstreken and Jan Sijbers and Toon Huysmans},
	editor = {Cassenti, Daniel N.}
}
@conference {1974,
	title = {Atom column detection from STEM images using the maximum a posteriori probability rule},
	year = {2019},
	author = {J Fatermans and Arnold Jan den Dekker and O{\textquoteright}Leary, C M. and Peter D Nellist and Sandra Van Aert}
}
@conference {1975,
	title = {Atom detection from electron microscopy images},
	year = {2019},
	pages = {15},
	author = {J Fatermans and Arnold Jan den Dekker and Sandra Van Aert}
}
@inproceedings {1852,
	title = {Automatic Generation of Statistical Shape Models in Motion},
	booktitle = {Advances in Human Factors in Simulation and Modeling (AHFE 2018)},
	volume = {780},
	year = {2019},
	pages = {170{\textendash}178},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Statistical body shape modeling (SBSM) is a well-known technique to map out the variability of body shapes and is commonly used in 3D anthropometric analyses. In this paper, a new approach to integrate movement acquired by a motion capture system with a body shape is proposed. This was done by selecting landmarks on a body shape model, and predicting a body shape based on features. Then, a virtual skeleton was generated relative to those landmarks. This skeleton was parented to a body shape, allowing to modify its pose and to add pre-recorded motion to different body shapes in a realistic way.},
	isbn = {978-3-319-94223-0},
	doi = {10.1007/978-3-319-94223-0_16},
	author = {Femke Danckaers and Scataglini, Sofia and Haelterman, Robby and Van Tiggelen, Damien and Toon Huysmans and Jan Sijbers},
	editor = {Cassenti, Daniel N.}
}
@conference {1993,
	title = {Beyond the consensus: is sacrificing part of the PCASL scan time for measurement of labeling efficiency and T1 of blood beneficial?},
	year = {2019},
	author = {Piet Bladt and M.J.P van Osch and Eric Achten and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1994,
	title = {Beyond the consensus: should measurement of T1 of blood and labeling efficiency be included and should a single- or multi-PLD protocol be used in a five-minute protocol for PCASL?},
	year = {2019},
	author = {Piet Bladt and M.J.P van Osch and Eric Achten and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1992,
	title = {Beyond the consensus: what to include when 5 minutes are available for perfusion imaging by PCASL?},
	year = {2019},
	author = {Piet Bladt and M.J.P van Osch and Eric Achten and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1941,
	title = {Brain ventricular volume changes induced by long-duration spaceflight},
	journal = {Proceedings of the National Academy of Sciences},
	volume = {116},
	year = {2019},
	pages = {10531-10536},
	abstract = {Long-duration spaceflight induces detrimental changes in human physiology due to microgravity. One example is a cephalic fluid shift. Here, we prospectively investigated the quantitative changes in cerebrospinal fluid (CSF) volume of the brain ventricular regions in space crew by means of a region of interest, observer-independent analysis on structural brain MRI scans. MRI scans were collected before the mission, shortly after and 7 mo after return to Earth. We found a significant increase in lateral and third ventricles at postflight and a trend to normalization at follow-up, but still significantly increased ventricular volumes. The observed spatiotemporal pattern of CSF compartment enlargement and recovery points to a reduced CSF resorption in microgravity as the underlying cause.Long-duration spaceflight induces detrimental changes in human physiology. Its residual effects and mechanisms remain unclear. We prospectively investigated the changes in cerebrospinal fluid (CSF) volume of the brain ventricular regions in space crew by means of a region of interest analysis on structural brain scans. Cosmonaut MRI data were investigated preflight (n = 11), postflight (n = 11), and at long-term follow-up 7 mo after landing (n = 7). Post hoc analyses revealed a significant difference between preflight and postflight values for all supratentorial ventricular structures, i.e., lateral ventricle (mean \% change {\textpm} SE = 13.3 {\textpm} 1.9), third ventricle (mean \% change {\textpm} SE = 10.4 {\textpm} 1.1), and the total ventricular volume (mean \% change {\textpm} SE = 11.6 {\textpm} 1.5) (all P \&lt; 0.0001), with higher volumes at postflight. At follow-up, these structures did not quite reach baseline levels, with still residual increases in volume for the lateral ventricle (mean \% change {\textpm} SE = 7.7 {\textpm} 1.6; P = 0.0009), the third ventricle (mean \% change {\textpm} SE = 4.7 {\textpm} 1.3; P = 0.0063), and the total ventricular volume (mean \% change {\textpm} SE = 6.4 {\textpm} 1.3; P = 0.0008). This spatiotemporal pattern of CSF compartment enlargement and recovery points to a reduced CSF resorption in microgravity as the underlying cause. Our results warrant more detailed and longer longitudinal follow-up. The clinical impact of our findings on the long-term cosmonauts{\textquoteright} health and their relation to ocular changes reported in space travelers requires further prospective studies.},
	issn = {0027-8424},
	doi = {10.1073/pnas.1820354116},
	url = {https://www.pnas.org/content/early/2019/05/01/1820354116},
	author = {Angelique Van Ombergen and Steven Jillings and Ben Jeurissen and Tomilovskaya, Elena and Alena Rumshiskaya and Liudmila Litvinova and Nosikova, Inna and Ekaterina V. Pechenkova and Ilya Rukavishnikov and Manko, Olga and Danylichev, Sergey and R{\"u}hl, R. Maxine and Inessa B. Kozlovskaya and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Steven S L Laureys and Jan Sijbers and zu Eulenburg, Peter and Floris L Wuyts}
}
@inproceedings {2090,
	title = {CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	pages = {1-5},
	address = {Padova, Italy},
	author = {Alice Presenti and Jan Sijbers and Arnold Jan den Dekker and Jan De Beenhouwer}
}
@conference {1984,
	title = {A deep learning approach to T1 mapping in quantitative MRI},
	volume = {32 (Suppl. 1)},
	number = {S09.05},
	year = {2019},
	publisher = {Magn Reson Mater Phy},
	abstract = {Quantitative MRI aims to measure biophysical tissue parameters through the analysis of the MR signal. Conventional parameter estimation methods, which often rely on a voxel-wise mapping, ignores spatial redundancies. In this work, a deep learning method for T1 mapping is proposed to overcome this limitation.},
	doi = {10.1007/s10334-019-00754-2},
	author = {Ribeiro Sabidussi, Emanoel and Michele Nicastro and Shabab Bazrafkan and Quinten Beirinckx and Ben Jeurissen and Jan Sijbers and Arnold Jan den Dekker and Stefan Klein and Dirk H J Poot}
}
@conference {1965,
	title = {Deep learning based missing wedge artefact removal for electron tomography},
	year = {2019},
	pages = {660-661},
	author = {Juho Rimpelainen and Shabab Bazrafkan and Jan Sijbers and Jan De Beenhouwer}
}
@inbook {1961,
	title = {Design smart clothing using digital human models},
	booktitle = {DHM and Posturography},
	year = {2019},
	pages = {683-698},
	publisher = {Academic Press},
	organization = {Academic Press},
	doi = {https://doi.org/10.1016/B978-0-12-816713-7.00053-2},
	author = {Scataglini, Sofia and Femke Danckaers and Toon Huysmans and Jan Sijbers and Giuseppe Andreoni}
}
@mastersthesis {1930,
	title = {The Development of 3D Statistical Shape Models for Diverse Applications},
	volume = {PhD in Sciences},
	year = {2019},
	type = {PhD thesis},
	author = {Femke Danckaers}
}
@article {1776,
	title = {Diffusion MRI fiber tractography of the brain},
	journal = {NMR in Biomedicine},
	year = {2019},
	doi = {10.1002/nbm.3785},
	author = {Ben Jeurissen and Maxime Descoteaux and Susumu Mori and Alexander Leemans}
}
@conference {1981,
	title = {Diffusion time dependence in the mid-time regime: a simulation study using PGSE.},
	number = {3572},
	year = {2019},
	address = {Montreal, Canada},
	abstract = {The purpose of this work is to study the effect of varying the diffusion time on the estimation of the parameters of the two-compartment diffusion tensor model in the mid-time regime. Simulation results show that the precision of the diffusion time-dependent compartmental parameter estimates increases when a variable echo time acquisition scheme is used. At low SNR, however, including diffusion time-dependence may lead to a high bias and variance compared to the more conventional non diffusion time-dependent model.},
	author = {Annelinde E. Buikema and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {1945,
	title = {Dynamic angle selection for few-view X-ray inspection of CAD based objects},
	booktitle = {Proc. SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)},
	volume = {11072},
	year = {2019},
	doi = {https://doi.org/10.1117/12.2534894},
	author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer}
}
@conference {1921,
	title = {Effect of diffusion time dependence on parameter estimation in the clinical time frame: a simulation study using PGSE},
	year = {2019},
	address = {Leiden, the Netherlands},
	abstract = {Fieremans et al. modelled the diffusion time dependence of diffusion longitudinal and transverse to white matter tracts, which can be interpreted as an effect of structural disorder at the mesoscopic scale. To our knowledge, this diffusion time-dependent (DT-dependent) model has not yet been studied in the mid-time regime (Δ=20-180ms) with varying echo times, which would be valuable for clinical practice. In this simulation study, we use the pulsed-gradient spin-echo (PGSE) sequence5 and study the effects of varying the diffusion time on the parameter estimation in a mid-time regime.},
	author = {Annelinde E. Buikema and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {1883,
	title = {Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_48.pdf},
	author = {Eline Janssens and Jan Sijbers and Manuel Dierick and Jan De Beenhouwer}
}
@inproceedings {1946,
	title = {Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction},
	booktitle = {15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)},
	volume = {11072},
	year = {2019},
	doi = {http://dx.doi.org/10.1117/12.2534836},
	author = {Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1918,
	title = {An Interactive Visual Comparison Tool for 3D Volume Datasets represented by Nonlinearly Scaled 1D Line Plots through Space-filling Curves},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	author = {Johannes Weissenb{\"o}ck and Bernhard Fr{\"o}hler and Eduard Gr{\"o}ller and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers and Santhosh Ayalur Karunakaran and Helmuth Hoeller and Johann Kastner and Christoph Heinzl}
}
@inproceedings {1989,
	title = {Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging},
	booktitle = {15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	volume = {11072},
	year = {2019},
	pages = {187 {\textendash} 190},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	keywords = {image reconstruction, Monte-Carlo simulation, SPECT I-123 brain imaging, System response modeling, Variance reduction technique (forced detection)},
	doi = {10.1117/12.2534881},
	url = {https://doi.org/10.1117/12.2534881},
	author = {Benjamin Auer and Navid Zeraatkar and Jan De Beenhouwer and Kesava Kalluri and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@conference {1990,
	title = {Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging},
	year = {2019},
	month = {2019},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Navid Zeraatkar and Arda K{\"o}nik and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@inproceedings {1851,
	title = {Latent Heat Loss of a Virtual Thermal Manikin for Evaluating the Thermal Performance of Bicycle Helmets},
	booktitle = {Advances in Human Factors in Simulation and Modeling},
	year = {2019},
	pages = {66{\textendash}78},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Thermal performance of three bicycle helmets for latent heat loss was evaluated through a virtual testing methodology using Computational fluid dynamics (CFD) simulations. The virtual thermal manikin was prescribed with a constant sweat rate of 2~g/h and a constant sweat film thickness of 0.3~mm. The simulations were carried out at 6~m/s until convergence was achieved. The results from steady state simulations show heat loss of 158~W from manikin without helmet and approximately 135~W with helmets. However, the thermal performance of helmets with a sweating manikin has been reduced from 89{\textendash}93{\%} to 84{\textendash}87{\%}. These results imply that evaporative/latent heat loss plays a significant role in thermal performance of helmets. Therefore, thermal performance tests for helmets should also include testing of helmets for evaporative heat loss.},
	isbn = {978-3-319-94223-0},
	author = {Mukunthan, Shriram and Jochen Vleugels and Toon Huysmans and Guido De Bruyne},
	editor = {Cassenti, Daniel N.}
}
@inproceedings {1885,
	title = {A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_54.pdf},
	author = {Van Nguyen and Jan De Beenhouwer and Joaquim Sanctorum and Sam Van Wassenbergh and Peter Aerts and Joris J. J. Dirckx and Jan Sijbers}
}
@article {1914,
	title = {Matlab{\textregistered} toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling},
	journal = {Computers in Biology and Medicine},
	volume = {105},
	year = {2019},
	pages = {27-38},
	doi = {10.1016/j.compbiomed.2018.12.008},
	author = {Keustermans, William and Toon Huysmans and Bert Schmelzer and Jan Sijbers and Joris J. J. Dirckx}
}
@article {1925,
	title = {The maximum a posteriori probability rule for atom column detection from HAADF STEM images},
	journal = {Ultramicroscopy},
	volume = {201},
	year = {2019},
	pages = {81-91},
	abstract = {Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.},
	keywords = {Atom detectability, Atom detection, Model selection, Scanning transmission electron microscopy (STEM)},
	issn = {0304-3991},
	doi = {https://doi.org/10.1016/j.ultramic.2019.02.003},
	url = {http://www.sciencedirect.com/science/article/pii/S0304399118304236},
	author = {J Fatermans and Sandra Van Aert and Arnold Jan den Dekker}
}
@article {1944,
	title = {Methods for characterization and optimisation of measuring performance of stereoscopic x-ray systems with image intensifiers},
	journal = {Measurement Science and Technology},
	volume = {30},
	year = {2019},
	doi = {https://doi.org/10.1088/1361-6501/ab23e7},
	author = {Joaquim Sanctorum and Dominique Adriaens and Joris J. J. Dirckx and Jan Sijbers and Chris Van Ginneken and Peter Aerts and Sam Van Wassenbergh}
}
@conference {1952,
	title = {Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images},
	year = {2019},
	month = {07/2019},
	abstract = {For the study of glass fiber-reinforced polymers (GFRP), {\textmu}CT is the method of choice. Obtaining
GFRP parameters from a {\textmu}CT scan is difficult, due to the presence of noise and artifacts. We propose a method
to improve GFRP image quality using a recently introduced deep neural network. We describe the network{\textquoteright}s
setup and the data generation and show how the trained network improves the reconstruction.},
	author = {Tim Elberfeld and Shabab Bazrafkan and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1873,
	title = {Moving Statistical Body Shape Models Using Blender},
	booktitle = {Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)},
	year = {2019},
	pages = {28{\textendash}38},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {In this paper, we present a new framework to integrate movement acquired by a motion capture system to a statistical body shape model using Blender. This provides a visualization of a digital human model based upon anthropometry and biomechanics of the subject. A moving statistical body shape model helps to visualize physical tasks with inter-individual variability in body shapes as well as anthropometric dimensions. This parametric modeling approach is useful for reliable prediction and simulation of the body shape movement of a specific population with a few given predictors such as stature, body mass index and age.},
	isbn = {978-3-319-96077-7},
	doi = {10.1007/978-3-319-96077-7_4},
	author = {Scataglini, Sofia and Femke Danckaers and Haelterman, Robby and Toon Huysmans and Jan Sijbers},
	editor = {Bagnara, Sebastiano and Tartaglia, Riccardo and Albolino, Sara and Alexander, Thomas and Fujita, Yushi}
}
@article {1963,
	title = {MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation.},
	journal = {Neuroimage},
	year = {2019},
	month = {2019 Aug 29},
	pages = {116137},
	abstract = {<p>MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.</p>},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2019.116137},
	author = {Tournier, J-Donald and Smith, Robert and Raffelt, David and Tabbara, Rami and Dhollander, Thijs and Pietsch, Maximilian and Christiaens, Daan and Ben Jeurissen and Yeh, Chun-Hung and Connelly, Alan}
}
@inproceedings {1853,
	title = {Multi-patch B-Spline Statistical Shape Models for CAD-Compatible Digital Human Modeling},
	booktitle = {Advances in Human Factors in Simulation and Modeling},
	year = {2019},
	pages = {179{\textendash}189},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Parametric 3D human body models are valuable tools for ergonomic product design and statistical shape modelling (SSM) is a powerful technique to build realistic body models from a database of 3D scans. Like the underlying 3D scans, body models built from SSMs are typically represented with triangle meshes. Unfortunately, triangle meshes are not well supported by CAD software where spline geometry dominates. Therefore, we propose a methodology to convert databases of pre-corresponded triangle meshes into multi-patch B-spline SSMs. An evaluation on four 3D scan databases shows that our method is able to generate accurate and water-tight models while preserving inter-subject correspondences by construction. In addition, we demonstrate that such SSMs can be used to generate design manikins which can be readily used in SolidWorks for designing well conforming product parts.},
	isbn = {978-3-319-94223-0},
	doi = {10.1007/978-3-319-94223-0_17},
	author = {Toon Huysmans and Femke Danckaers and Jochen Vleugels and Daniel Lacko and Guido De Bruyne and Stijn Verwulgen and Jan Sijbers}
}
@conference {1982,
	title = {Optimal design of a blended diffusion/relaxometry experiment},
	year = {2019},
	address = {Rotterdam, the Netherlands},
	author = {Annelinde E. Buikema and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1973,
	title = {poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT},
	journal = {Optics Express},
	volume = {27},
	year = {2019},
	pages = {33427-33435},
	doi = {https://doi.org/10.1364/OE.27.033670},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@article {1893,
	title = {Posture normalization of 3D body scans},
	journal = {Ergonomics},
	volume = {62},
	year = {2019},
	pages = {834-848},
	doi = {10.1080/00140139.2019.1581262},
	author = {Femke Danckaers and Toon Huysmans and Ann Hallemans and Guido De Bruyne and Steven Truijen and Jan Sijbers}
}
@inproceedings {1988,
	title = {Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2019},
	month = {11/2019},
	address = {Manchester, UK},
	author = {Benjamin Auer and Jan De Beenhouwer and Navid Zeraatkar and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@article {2085,
	title = {Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT},
	journal = {Physics in Medicine \& Biology},
	volume = {64},
	year = {2019},
	pages = {245001},
	abstract = {Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy (>300 keV,  2.5\% abundance) gamma photons in addition to the primary emission (159 keV, 83\% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson{\textquoteright}s Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15\% photopeak window. The total scatter fraction for LEHR was 56\% where the largest contribution came from the high-energy scatter from the back compartments (31\%). For the same energy window, the total scatter for MPH was 21\% with only 1\% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging.},
	doi = {10.1088/1361-6560/ab58fe},
	url = {https://doi.org/10.1088\%2F1361-6560\%2Fab58fe},
	author = {Arda K{\"o}nik and Benjamin Auer and Jan De Beenhouwer and Kesava Kalluri and Navid Zeraatkar and Lars R. Furenlid and Michael A. King}
}
@conference {1959,
	title = {Quantifying 3D atomic structures of nanomaterials and their dynamics using model-based scanning transmission electron microscopy},
	year = {2019},
	author = {Sandra Van Aert and De wael, A and J Fatermans and Ivan Lobato and Annick De Backer and Jones, L and Arnold Jan den Dekker and Peter D Nellist}
}
@conference {2020,
	title = {Robust outlier detection for diffusion kurtosis MRI based on IRLLS},
	volume = {32},
	number = {1},
	year = {2019},
	url = {https://link.springer.com/article/10.1007/s10334-019-00756-0},
	author = {Vincenzo Anania and Thibo Billiet and Ben Jeurissen and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {1884,
	title = {Simulated grating-based x-ray phase contrast images of CFRP-like objects},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	pages = {1-8},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_45.pdf},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Johannes Weissenb{\"o}ck and Christoph Heinzl and Johann Kastner and Jan Sijbers}
}
@conference {1958,
	title = {Strategies for quantifying 3D atomic structures of nanomaterials and their dynamics using dose-efficient ADF STEM},
	year = {2019},
	author = {Sandra Van Aert and De wael, A and J Fatermans and Ivan Lobato and Annick De Backer and Jones, L and Arnold Jan den Dekker and Peter D Nellist}
}
@conference {Dhondt2019-jv,
	title = {Structural adaptations of cognitive emotional brain regions are linked to endogenous pain modulation: a psychophysical and brain imaging study in healthy people and in low back pain},
	year = {2019},
	pages = {399},
	author = {Dhondt, E and Ben Jeurissen and Danneels, L and Van Oosterwijck, J}
}
@conference {1983,
	title = {Super-resolution T1 mapping with integrated motion compensation in a joint maximum likelihood framework},
	volume = {32 (Suppl. 1)},
	number = {S14.05},
	year = {2019},
	publisher = {Magn Reson Mater Phy},
	abstract = {To date, 3D high resolution (HR) quantitative T1 mapping is not feasible in clinical practice due to prohibitively long acquisition times. Recent work has shown that super-resolution reconstruction (SRR), in which a 3D HR T1 map is directly estimated from a set of low through-plane resolution (LR) multi-slice (ms) T1-weighted (T1w) images with different slice orientations, can improve the trade-off between SNR, spatial resolution, and acquisition time. In that work, however, inter-image motion compensation for SRR is performed in a preprocessing step in which the transformation parameters of each LR image are updated after image registration. As a result, potential registration errors might propagate in the T1 estimation as no feedback mechanism is in place. Moreover, due to missing subvoxel accuracy no HR information is readily available during preprocessing. In the current work, we explore the potential of an improved SRR T1 mapping method that aims at more accurate T1 maps by combining T1 and motion estimation in a joint Maximum Likelihood estimation (jMLE) framework.
},
	doi = {10.1007/s10334-019-00754-2},
	author = {Quinten Beirinckx and Ben Jeurissen and Marleen Verhoye and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {1917,
	title = {Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_52.pdf},
	author = {Bernhard Fr{\"o}hler and Lucas da Cunha Melo and Johannes Weissenb{\"o}ck and Johann Kastner and Torsten M{\"o}ller and Hans-Christian Hege and Eduard Gr{\"o}ller and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers and Christoph Heinzl}
}
@conference {1980,
	title = {A Trajectory Based Bottom-Up Volume Reconstruction Method for Atom Probe Tomography},
	year = {2019},
	author = {Yu-Ting Ling and Siegfried Cools and Jan De Beenhouwer and Jan Sijbers and Wilfried Vandervorst}
}
@inproceedings {1874,
	title = {Using 3D Statistical Shape Models for Designing Smart Clothing},
	booktitle = {Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)},
	year = {2019},
	pages = {18{\textendash}27},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {In this paper we present an innovative approach to design smart clothing using statistical body shape modeling (SBSM) from the CAESAR{\texttrademark} dataset. A combination of different digital technologies and applications are used to create a common co-design workflow for garment design. User and apparel product design and developers can get personalized prediction of cloth sizing, fitting and aesthetics.},
	isbn = {978-3-319-96077-7},
	doi = {10.1007/978-3-319-96077-7_3},
	author = {Scataglini, Sofia and Femke Danckaers and Haelterman, Robby and Toon Huysmans and Jan Sijbers and Andreoni, Giuseppe},
	editor = {Bagnara, Sebastiano and Tartaglia, Riccardo and Albolino, Sara and Alexander, Thomas and Fujita, Yushi}
}
@article {1923,
	title = {A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science},
	journal = {Computer Graphics Forum},
	volume = {38},
	year = {2019},
	pages = {273-283},
	doi = {10.1111/cgf.13688},
	author = {Bernhard Fr{\"o}hler and Tim Elberfeld and Torsten M{\"o}ller and Johannes Weissenb{\"o}ck and Jan De Beenhouwer and Jan Sijbers and Hans-Christian Hege and Johann Kastner and Christoph Heinzl}
}
@conference {2022,
	title = {Voxelwise harmonisation of FA on a cohort of 605 healthy subjects using ComBat: an exploratory study},
	year = {2019},
	author = {Maira Siqueira Pinto and Roberto Paolella and Thibo Billiet and Pieter Van Dyck and Pieter-Jan Guns and Ben Jeurissen and Annemie Ribbens and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2000,
	title = {Women{\textquoteright}s preferences for male facial masculinity are not condition-dependent in a large online study},
	journal = {The All Results Journals: Biol},
	volume = {10},
	year = {2019},
	type = {				 A3 Journal article },
	abstract = {While several studies have found evidence for conditional-dependent effect on women{\textquoteright}s preferences for male masculinity, others have questioned the relative importance of these effects. In this study, we evaluated variation in women{\textquoteright}s preference for male facial masculinity in a forced-choice experiment. Nearly 1200 participants scored preference for manipulated photos and surface scans. Between-individual variation in preferences were relatively small, especially for the evaluation of the surface scans. Nevertheless, preferences from the evaluations of photos and scans correlated positively, indicating that both stimuli provide similar biological information. Only few condition-dependent variables correlated significantly with preference for masculinity, and not all in predicted directions. Stronger preference for masculine male faces {\textendash} albeit only significant for the photos {\textendash} with higher own women attractiveness was observed as expected. Yet, for perceived infectability, consistently across the photos and scans, a negative association with preference for masculine faces was observed, which is opposite to theoretical predictions. In addition, no effects of pathogen exposure, germ aversion (a correlate of disgust), relational status, preference for short term relationships and sociosexuality were detected. Thus, overall, our study is in line with recent large studies that also find only very weak conditiondependent effects, if any.},
	issn = {21724784},
	author = {Van Dongen, Stefan and Femke Danckaers and Beerten, Jessie and Toon Huysmans}
}
@conference {1995,
	title = {Absolute CBF quantification in multi-time point ASL: the T1 issue},
	year = {2018},
	author = {Piet Bladt and Arnold Jan den Dekker and Clement, Patricia and Eric Achten and Jan Sijbers}
}
@conference {1827,
	title = {Accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation},
	year = {2018},
	pages = {5664},
	address = {Paris, France},
	author = {Gabriel Ramos-Llord{\'e}n and Quinten Beirinckx and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1857,
	title = {Advanced X-ray tomography: experiment, modeling, and algorithms},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	pages = {080101},
	doi = {https://doi.org/10.1088/1361-6501/aacd25},
	author = {Kees Joost Batenburg and Francesco De Carlo and Lucia Mancini and Jan Sijbers}
}
@mastersthesis {1867,
	title = {Advances in X-ray reconstruction algorithms for limited data problems in conventional and non-conventional projection geometries},
	volume = {PhD in Sciences / Physics},
	year = {2018},
	type = {PhD thesis},
	author = {Eline Janssens}
}
@conference {1890,
	title = {Bayesian analysis of noisy scanning transmission electron microscopy images for single atom detection},
	year = {2018},
	pages = {95},
	author = {J Fatermans and Arnold Jan den Dekker and M{\"u}ller-Caspary, K and Ivan Lobato and Sandra Van Aert}
}
@conference {1949,
	title = {Changes in intrinsic functional brain connectivity after first-time exposure to parabolic flight},
	year = {2018},
	doi = {10.3389/conf.fphys.2018.26.00017},
	author = {Angelique Van Ombergen and Floris L Wuyts and Ben Jeurissen and Jan Sijbers and Floris Vanhevel and Steven Jillings and Paul M Parizel and Stefan Sunaert and Paul H Van de Heyning and Vincent Dousset and Steven S L Laureys and Athena Demertzi}
}
@article {1901,
	title = {Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform},
	journal = {ISPRS Journal of Photogrammetry and Remote Sensing },
	volume = {138},
	year = {2018},
	pages = {121-138},
	author = {Mohd Shahrimie Mohd Asaari and Puneet Mishra and Stien Mertens and Stijn Dhondt and Dirk Inze and Nathalie Wuyts and Paul Scheunders}
}
@inproceedings {1770,
	title = {A Combined Statistical Shape Model of the Scalp and Skull of the Human Head},
	booktitle = { 8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017)},
	volume = {591},
	year = {2018},
	pages = {538-548},
	publisher = {Springer},
	organization = {Springer},
	address = {Los Angeles, California, USA},
	doi = {10.1007/978-3-319-60591-3_49},
	author = {Femke Danckaers and Daniel Lacko and Stijn Verwulgen and Guido De Bruyne and Toon Huysmans and Jan Sijbers}
}
@inproceedings {1831,
	title = {Comparative Visualization of Orientation Tensors in Fiber-Reinforced Polymers},
	booktitle = {8th Conference on Industrial Computed Tomography, Wels, Austria },
	year = {2018},
	author = {Johannes Weissenb{\"o}ck and M Arikan and D Salaberger and Johann Kastner and Jan De Beenhouwer and Jan Sijbers and S Rauchenzauner and T Raab-Wernig and E Gr{\"o}ller and Christoph Heinzl}
}
@inproceedings {1898,
	title = {Detection of plant responses to drought using close-range hyperspectral imaging in a high-throughput phenotyping platform},
	booktitle = {IEEE Whispers 2018, Workshop on Hyperspectral Image and Signal Processing, Amsterdam, 23-26 September  },
	year = {2018},
	author = {Mohd Shahrimie Mohd Asaari and Stien Mertens and S Dhondt and Nathalie Wuyts and Paul Scheunders}
}
@article {1817,
	title = {Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology.},
	journal = {Alzheimer{\textquoteright}s Research \& Therapy },
	volume = {10},
	year = {2018},
	pages = {1-16},
	doi = {10.1186/s13195-017-0329-8},
	author = {Jelle Praet and Nikolay Manyakov and Leacky Muchene and Zhenhua Mai and Vasilis Terzopoulos and Steve De Backer and An Torremans and Pieter-Jan Guns and Tom Van De Casteele and Astrid Bottelbergs and Bianca Van Broeck and Jan Sijbers and Dirk Smeets and Ziv Shkedy and Luc Bijnens and Darrel Pemberton and Mark Schmidt and Annemie Van Der Linden and Marleen Verhoye}
}
@article {1820,
	title = {Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach},
	journal = {Magnetic Resonance in Medicine},
	volume = {80},
	year = {2018},
	pages = {802-813},
	doi = {10.1002/mrm.27075},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Floris Vanhevel and Pim Pullens and Paul M Parizel and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1828,
	title = {An educational presentation on accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation},
	year = {2018},
	address = {Antwerp, Belgium},
	abstract = {MRI relaxometry holds the promise of providing biomarkers for monitoring, staging and follow up of diseases. Imperative to meet minimum standards for objective, reproducible, and reliable biomarkers is the need for accurate, precise, quantitative parameters maps, such as T1~or T2. While unrealistic physical modelling is often argued as the main cause of lack of accuracy, little effort has been made on discussing the impact that inadequate parameter estimation methods have on the accuracy and precision of MRI relaxometry techniques. This educational poster attempts to introduce young MR students/researchers into the basics of modern statistical parameter estimation theory, and its application for accurate and precise relaxometry. 
},
	author = {Gabriel Ramos-Llord{\'e}n and Quinten Beirinckx and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {1830,
	title = {An efficient CAD projector for X-ray projection based 3D inspection with the ASTRA Toolbox},
	booktitle = {8th Conference on Industrial Computed Tomography, Wels, Austria},
	year = {2018},
	author = {{\'A}rp{\'a}d Marinovszki and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1769,
	title = {Full Body Statistical Shape Modeling with Posture Normalization},
	booktitle = {The 8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017)},
	volume = {591},
	year = {2018},
	pages = {437-448},
	publisher = {Springer},
	organization = {Springer},
	address = {Los Angeles, California, USA},
	doi = {10.1007/978-3-319-60591-3_39},
	author = {Femke Danckaers and Toon Huysmans and Ann Hallemans and Guido De Bruyne and Steven Truijen and Jan Sijbers}
}
@article {1912,
	title = {High quality statistical shape modelling of the human nasal cavity and applications},
	journal = {Royal Society Open Science},
	volume = {5},
	year = {2018},
	doi = {https://doi.org/10.1098/rsos.181558},
	author = {Keustermans, William and Toon Huysmans and Femke Danckaers and Andrzej Zarowski and Bert Schmelzer and Jan Sijbers and Joris J. J. Dirckx}
}
@mastersthesis {1832,
	title = {Improved MRI Relaxometry through Statistical Signal Processing},
	volume = { Doctor of Science},
	year = {2018},
	month = {02/2018},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	abstract = {Magnetic Resonance Imaging (MRI) relaxometry is a quantitative MRI modality that deals with the estimation of the spin-lattice, T1, and the spin-spin, T2, relaxation times. Both relaxation times are fundamental parameters that describe the spin dynamics within a tissue during the relaxation process of the Nuclear Magnetic Resonance (NMR) phenomenon. During the last decades, spatial T1 and T2 maps have been analyzed to study and monitor the states of a multitude of human diseases. Those studies have shown that MRI relaxometry holds the promise of generating robust, objective image-based biomarkers for central nervous system pathologies, cardiovascular diseases and beyond. Unfortunately, quantitative biomarkers derived from MRI relaxometry are not yet sufficiently specific, sensitive, and robust to be routinely used in clinical practice. On top of that, high-resolution relaxation maps demand a clinically unfeasible long scanning time.

This PhD thesis tries to reduce the obstacles that preclude MRI relaxometry from being a fast, accurate, and precise quantitative MRI modality for clinical use by improving the way MR relaxometry data are acquired, processed and analyzed. In particular, by adopting a statistical signal processing approach, three contributions that address common problems of the field are given. Firstly, we present a unified relaxometry-based processing framework where the T1 map estimation and motion correction are accounted for in a synergistic manner, being both the T1 map and the motion parameters simultaneously estimated with a Maximum-Likelihood estimator. It is demonstrated that substantially more accurate T1 maps are obtained with our proposed integrated approach in comparison to the yet typical but suboptimal two-step approach: T1 model fitting after image registration.  Secondly, we developed a fast, robust, T1 estimator for Variable Flip Angle (VFA) T1 mapping that can provide statistically optimal T1 estimates with unprecedentedly short computation time, thereby enabling optimal, real-time, VFA T1 mapping.  Finally, we were able to reduce the long overall scanning time of MRI relaxometry studies using our novel k-space reconstruction technique that permits the reconstruction of individual MR images with less number of samples than it is commonly required.},
	author = {Gabriel Ramos-Llord{\'e}n}
}
@conference {1860,
	title = {Investigating the relationship between shape and flow in the human nose using a statistical shape model},
	year = {2018},
	url = {http://www.eccm-ecfd2018.org/admin/files/fileabstract/a781.pdf},
	author = {Keustermans, William and Toon Huysmans and Femke Danckaers and Andrzej Zarowski and Bert Schmelzer and Jan Sijbers and Joris J. J. Dirckx}
}
@inproceedings {1869,
	title = {Joint reconstruction and flat-field estimation using support estimation},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	address = {Sydney, Australia},
	doi = {10.1109/NSSMIC.2018.8824406},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Vincent Van Nieuwenhove and Wim Vanroose and Jan Sijbers}
}
@conference {1957,
	title = {Maximising dose efficiency in quantitative STEM to reveal the 3D atomic structure of nanomaterials},
	year = {2018},
	author = {Sandra Van Aert and J Fatermans and Annick De Backer and van den Bos, K. H. W. and O{\textquoteright}Leary, C M. and M{\"u}ller-Caspary, K and Jones, L and Ivan Lobato and B{\'e}ch{\'e}, A and Arnold Jan den Dekker and Sara Bals and Peter D Nellist}
}
@conference {1891,
	title = {The maximum a posteriori probability rule to detect single atoms from low signal-to-noise ratio scanning transmission electron microscopy images},
	year = {2018},
	author = {J Fatermans and Arnold Jan den Dekker and M{\"u}ller-Caspary, K and Ivan Lobato and Sandra Van Aert}
}
@article {1816,
	title = {Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	doi = {10.1088/1361-6501/aa9de3},
	author = {Eline Janssens and Jan De Beenhouwer and Mattias Van Dael and Thomas De Schryver and Luc Van Hoorebeke and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@article {1866,
	title = {A new data structure and workflow for using 3D anthropometry in the design of wearable products},
	journal = {International Journal of Industrial Ergonomics},
	volume = {64},
	year = {2018},
	pages = {108 - 117},
	keywords = {3D anthropometry, CAD, EEG headsets, Mass-customization, Parameterized design, Statistical shape models},
	issn = {0169-8141},
	doi = {https://doi.org/10.1016/j.ergon.2018.01.002},
	url = {http://www.sciencedirect.com/science/article/pii/S0169814117302342},
	author = {Stijn Verwulgen and Daniel Lacko and Jochen Vleugels and Kristof Vaes and Femke Danckaers and Guido De Bruyne and Toon Huysmans}
}
@article {1842,
	title = {NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {37},
	year = {2018},
	pages = {2414 - 2427},
	doi = {10.1109/TMI.2018.2833288},
	author = {Gabriel Ramos-Llord{\'e}n and Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcus Bj{\"o}rk and Floris Vanhevel and Paul M Parizel and Raul San Jos{\'e} Est{\'e}par and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1847,
	title = {Parametric Reconstruction of Advanced Glass Fiber-reinforced Polymer Composites from X-ray Images},
	year = {2018},
	address = {Wels, Austria},
	abstract = {A novel approach to the reconstruction of glass fiber-reinforced polymers (GFRP) from X-ray micro-computed tomography
(μCT) data is presented. The traditional fiber analysis workflow requires complete sample reconstruction, pre-processing and
segmentation, followed by the analysis of fiber distribution, orientation, and other features of interest. Each step in the chain
introduces errors that propagate through the pipeline and impair the accuracy of the estimation of those features. In the
approach presented in this paper, we combine iterative reconstruction techniques and a priori knowledge about the sample, to
reconstruct the volume and estimate the orientation of the fibers simultaneously. Fibers are modeled using rigid cylinders in
space whose orientation and position is then iteratively refined. The output of the algorithm is a non voxel-based dataset of the
fibers{\textquoteright} parametric representation, allowing to directly assess fiber features and distribution characteristics and to simulate the resulting material properties.},
	keywords = {GFRP, Materials Science, Modeling of Microstructures, Parametric Reconstruction, Tomography, {\textmu}CT},
	author = {Tim Elberfeld and Jan De Beenhouwer and Arnold Jan den Dekker and Christoph Heinzl and Jan Sijbers}
}
@article {1859,
	title = {Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study},
	journal = {Journal of Nondestructive Evaluation},
	volume = {37},
	year = {2018},
	month = {Jul},
	pages = {1573-4862},
	abstract = {We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating a priori knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available.},
	keywords = {GFRP, Glass fiber reinforced polymer, Materials Science, Modeling of micro-structures, Parametric model, Tomography, {\textmu}CT},
	doi = {10.1007/s10921-018-0514-0},
	url = {https://doi.org/10.1007/s10921-018-0514-0},
	author = {Tim Elberfeld and Jan De Beenhouwer and Arnold Jan den Dekker and Christoph Heinzl and Jan Sijbers}
}
@inproceedings {1833,
	title = {pDART: Discrete algebraic reconstruction using a polychromatic forward model},
	booktitle = {The Fifth International Conference on Image Formation  in X-Ray Computed Tomography},
	year = {2018},
	address = {Salt Lake City, Utah, USA},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1880,
	title = {Preliminary evaluation of surface mesh modeling of system geometry, anatomy phantom, and source activity for GATE simulations},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	month = {11/2018},
	address = {Sydney, Australia},
	author = {Benjamin Auer and Arda K{\"o}nik and Timothy J. Fromme and Kesava Kalluri and Jan De Beenhouwer and George I. Zubal and Lars R. Furenlid and Michael A. King}
}
@inproceedings {1879,
	title = {Preliminary investigation of design parameters of an innovative multi- pinhole system dedicated to brain SPECT imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	month = {11/2018},
	address = {Sydney, Australia},
	author = {Benjamin Auer and Jan De Beenhouwer and Timothy J. Fromme and Kesava Kalluri and Justin C. Goding and George I. Zubal and Lars R. Furenlid and Michael A. King}
}
@article {1935,
	title = {Principal component analysis as a tool for determining optimal tibial baseplate geometry in modern TKA design},
	journal = {Acta Orthop Belg},
	volume = {84},
	year = {2018},
	pages = {452-460},
	author = {Sare Huijs and Toon Huysmans and A De Jong and Nele Arnout and Jan Sijbers and Johan Bellemans}
}
@article {1903,
	title = {A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila},
	journal = {Plos Computational Biology},
	volume = {14},
	year = {2018},
	pages = {e1006410},
	author = {G Liu and Tanmay Nath and Z Guo and G Linneweber and A Claeys and J Li and M Bengochea and Steve De Backer and Barbara Weyn and M Sneyders and H Nicasy and P Yu and Paul Scheunders and Bassem Hassan}
}
@article {1877,
	title = {Simulations of a Multipinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging},
	journal = {IEEE Transactions on Radiation and Plasma Medical Sciences},
	volume = {2},
	year = {2018},
	month = {Sept},
	pages = {444-451},
	keywords = {Analytical models, Apertures, Brain, Collimators, Logic gates, multipinhole (MPH), Sensitivity, simulation, Single photon emission computed tomography, SPECT},
	issn = {2469-7311},
	doi = {10.1109/TRPMS.2018.2831208},
	author = {Arda K{\"o}nik and Jan De Beenhouwer and J. M. Mukherjee and Kesava Kalluri and S Banerjee and N Zeraatkar and Timothy J. Fromme and Michael A. King}
}
@conference {1920,
	title = {Simultaneous T2/diffusion estimation: do we need a diffusion time dependent diffusion model?},
	year = {2018},
	address = {Antwerp, Belgium},
	abstract = {Joint estimation of the transverse relaxation (T2) and the diffusion tensor allows for probing white matter integrity in a more efficient way compared to estimating these parameters from sequential relaxometry and diffusion imaging protocols. For simultaneous estimation of diffusion and relaxation parameters, short echo times are needed and, as a consequence, short diffusion times. Therefore we need a flexible diffusion model that accounts for diffusion time dependence. Currently used diffusion models do not account for this dependence. An acknowledged model describing the properties of diffusion in coherently oriented fiber populations is the diffusion tensor. Alternative models are proposed, which allow to resolve multiple fiber directions, such as multiple tensor fitting and estimation of the fiber orientation distribution function using high angular resolution data acquisition. When the diffusion time is kept short enough, the diffusion behavior reflects that of free diffusion, meaning that the diffusion tensor is isotropic. With increasing diffusion time, diffusion is hindered by extracellular and intracellular components and the diffusion tensor evolves towards an ellipsoid. To the authors{\textquoteright} knowledge there is no model available to correct for diffusion time dependence in clinically short range diffusion times, allowing joint estimation of relaxation and diffusion properties. This work provides an overview of the state-of-the-art and challenges of diffusion time dependent diffusion modeling.},
	author = {Annelinde E. Buikema and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1878,
	title = {Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images},
	journal = {Phys. Rev. Lett.},
	volume = {121},
	year = {2018},
	month = {Jul},
	pages = {056101},
	abstract = {Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.},
	doi = {10.1103/PhysRevLett.121.056101},
	url = {https://link.aps.org/doi/10.1103/PhysRevLett.121.056101},
	author = {J Fatermans and Arnold Jan den Dekker and M{\"u}ller-Caspary, K. and Ivan Lobato and O{\textquoteright}Leary, C. M. and Peter D Nellist and Sandra Van Aert}
}
@inproceedings {1897,
	title = {Spectral variability in a multilinear mixing model},
	booktitle = {IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27},
	year = {2018},
	author = {T Dox and Rob Heylen and Paul Scheunders}
}
@conference {Dhondt2018-hg,
	title = {Structural alterations of cognitive emotional brain regions are linked to the presence of spinal sensitization in low back pain},
	year = {2018},
	author = {Dhondt, Evy and Ben Jeurissen and Danneels, Lieven and Van Oosterwijck, Jessica}
}
@conference {Van_Dyck2018-st,
	title = {Super-resolution Reconstruction of Knee MRI},
	year = {2018},
	pages = {5184},
	author = {Pieter Van Dyck and Floris Vanhevel and De Smet, E and Paul M Parizel and Jan Sijbers and Ben Jeurissen}
}
@article {1865,
	title = {A three-dimensional digital neurological atlas of the mustached bat (Pteronotus parnellii)},
	journal = {NeuroImage},
	volume = {183},
	year = {2018},
	pages = {300-313},
	issn = {10538119},
	doi = {10.1016/j.neuroimage.2018.08.013},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811918307110https://api.elsevier.com/content/article/PII:S1053811918307110?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S1053811918307110?httpAccept=text/plain},
	author = {Washington, Stuart D. and Hamaide, Julie and Ben Jeurissen and Gwendolyn Van Steenkiste and Toon Huysmans and Jan Sijbers and Deleye, Steven and Kanwal, Jagmeet S. and De Groof, Geert and Liang, Sayuan and Johan Van Audekerke and Wenstrup, Jeffrey J. and Annemie Van Der Linden and Radtke-Schuller, Susanne and Marleen Verhoye}
}
@article {1838,
	title = {Three-dimensional quantitative analysis of healthy foot shape: a proof of concept study},
	journal = {Journal of Foot and Ankle Research},
	volume = {11},
	year = {2018},
	month = {Mar},
	pages = {1-13},
	abstract = {Background
Foot morphology has received increasing attention from both biomechanics researches and footwear manufacturers. Usually, the morphology of the foot is quantified by 2D footprints. However, footprint quantification ignores the foot{\textquoteright}s vertical dimension and hence, does not allow accurate quantification of complex 3D foot shape.

Methods
The shape variation of healthy 3D feet in a population of 31 adult women and 31 adult men who live in Belgium was studied using geometric morphometric methods. The effect of different factors such as sex, age, shoe size, frequency of sport activity, Body Mass Index (BMI), foot asymmetry, and foot loading on foot shape was investigated. Correlation between these factors and foot shape was examined using multivariate linear regression.

Results
The complex nature of a foot{\textquoteright}s 3D shape leads to high variability in healthy populations. After normalizing for scale, the major axes of variation in foot morphology are (in order of decreasing variance): arch height, combined ball width and inter-toe distance, global foot width, hallux bone orientation (valgus-varus), foot type (e.g. Egyptian, Greek), and midfoot width. These first six modes of variation capture 92.59\% of the total shape variation. Higher BMI results in increased ankle width, Achilles tendon width, heel width and a thicker forefoot along the dorsoplantar axis. Age was found to be associated with heel width, Achilles tendon width, toe height and hallux orientation. A bigger shoe size was found to be associated with a narrow Achilles tendon, a hallux varus, a narrow heel, heel expansion along the posterior direction, and a lower arch compared to smaller shoe size. Sex was found to be associated with differences in ankle width, Achilles tendon width, and heel width. Frequency of sport activity was associated with Achilles tendon width and toe height.

Conclusion
A detailed analysis of the 3D foot shape, allowed by geometric morphometrics, provides insights in foot variations in three dimensions that can not be obtained from 2D footprints. These insights could be applied in various scientific disciplines, including orthotics and shoe design.},
	issn = {1757-1146},
	doi = {10.1186/s13047-018-0251-8},
	url = {https://doi.org/10.1186/s13047-018-0251-8},
	author = {Kristina Stankovi{\'c} and Brian G Booth and Femke Danckaers and Fien Burg and Vermaelen, Philippe and Saartje Duerinck and Jan Sijbers and Toon Huysmans}
}
@article {1792,
	title = {TomoBank: A Tomographic Data Repository for Computational X-ray Science},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	pages = {1-10},
	doi = {https://doi.org/10.1088/1361-6501/aa9c19},
	author = {Francesco De Carlo and Doga Gursoy and Daniel Ching and Kees Joost Batenburg and Ludwig, Wolfgang and Lucia Mancini and Federica Marone Welford and Rajmund Mokso and Daan Pelt and Jan Sijbers and Mark Rivers}
}
@inproceedings {1858,
	title = {X-ray Phase-contrast Simulations of Fibrous Phantoms using GATE},
	booktitle = {2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)},
	year = {2018},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Sydney, Australia},
	doi = {10.1109/NSSMIC.2018.8824641},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@article {1712,
	title = {Atom-counting in High Resolution Electron Microscopy: TEM or STEM - that{\textquoteright}s the question},
	journal = {Ultramicroscopy},
	volume = {147},
	year = {2017},
	pages = {112{\textendash}120},
	doi = {http://dx.doi.org/10.1016/j.ultramic.2016.10.011},
	author = {Julie Gonnissen and Annick De Backer and Arnold Jan den Dekker and Jan Sijbers and Sandra Van Aert}
}
@article {1779,
	title = {Building 3D Statistical Shape Models of Horticultural Products},
	journal = {Food and Bioprocess Technology},
	volume = {10},
	year = {2017},
	pages = {2100-2112},
	doi = {10.1007/s11947-017-1979-z },
	author = {Femke Danckaers and Toon Huysmans and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@conference {Adnan2017-uz,
	title = {The chronification of pain: are peripheral muscle dysfunction linked to central alteration in the brain},
	year = {2017},
	author = {Adnan, Rahmat and Dhondt, Evy and Danneels, Lieven and Hodges, Paul and Ben Jeurissen and Van Oosterwijck, Jessica}
}
@conference {Adnan2017-sq,
	title = {The chronification of pain : are peripheral muscle dysfunctions linked to central alteration in the brain?},
	year = {2017},
	author = {Adnan, Rahmat and Dhondt, Evy and Danneels, Lieven and Hodges, Paul and Ben Jeurissen and Van Oosterwijck, Jessica}
}
@inproceedings {1771,
	title = {A Comparison Between Physical and Virtual Experiments of Convective Heat Transfer Between Head and Bicycle Helmet},
	booktitle = {8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017)},
	year = {2017},
	publisher = {Springer},
	organization = {Springer},
	address = {Los Angeles, California, USA},
	author = {Shriram Mukunthan and Kalev Kuklane and Toon Huysmans and Guido De Bruyne}
}
@article {1727,
	title = {Data-Driven Affine Deformation Estimation and Correction in Cone Beam Computed Tomography},
	journal = {IEEE Transactions on Image Processing},
	volume = {26},
	year = {2017},
	pages = {1441-1451},
	doi = {10.1109/TIP.2017.2651370},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Thomas De Schryver and Luc Van Hoorebeke and Jan Sijbers}
}
@conference {1889,
	title = {Detection of atomic columns from noisy STEM images},
	year = {2017},
	pages = {445-446},
	author = {J Fatermans and M{\"u}ller-Caspary, K and Arnold Jan den Dekker and Sandra Van Aert}
}
@conference {Van_Dyck2017-jo,
	title = {Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft},
	year = {2017},
	pages = {377},
	author = {Pieter Van Dyck and De Smet, Eline and Froeling, Martijn and Peter Verdonk and Torfs, Micha{\"e}l and Pim Pullens and Jan Sijbers and Paul M Parizel and Ben Jeurissen}
}
@article {1744,
	title = {Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft},
	journal = {Journal of Magnetic Resonance Imaging},
	volume = {46},
	year = {2017},
	pages = {1423{\textendash}1432},
	doi = {10.1002/jmri.25666},
	author = {Pieter Van Dyck and Martijn Froeling and Eline De Smet and Pim Pullens and Micha{\"e}l Torfs and Peter Verdonk and Jan Sijbers and Paul M Parizel and Ben Jeurissen}
}
@conference {1785,
	title = {Dual axis Dark Field Contrast Tomography for visualisation of scattering directions in a CFRP sample},
	year = {2017},
	pages = {79-80},
	address = {Z{\"u}rich, Switzerland},
	abstract = {In Carbon Fiber Reinforced Polymer (CFRP), the carbon fibers embedded into the polymer matrix cause scattering when inspected with X-rays. This scattering is captured within the dark field image when the sample is scanned with a grating based interferometer. The main disadvantage is, however, that only directional scattering information can be achieved due to the orientation of the gratings. By scanning the sample twice, with a 90 degrees rotation of the sample in between, information from two different scattering directions can be combined into one 3D reconstruction volume. In this abstract, such an approach is shown to improve the representation of scattering inside the sample.},
	keywords = {Dark field tomography, Dual axis, Phase contrast, Tomography, X-rays},
	url = {https://indico.psi.ch/getFile.py/access?resId=1\&materialId=2\&confId=5055},
	author = {Eline Janssens and Jan De Beenhouwer and Jonathan Sanctorum and Sascha Senck and Christoph Heinzl and Jan Sijbers}
}
@article {1756,
	title = {The effect of spaceflight and microgravity on the human brain},
	journal = {Journal of Neurology},
	volume = {246},
	year = {2017},
	pages = {18-22},
	doi = {10.1007/s00415-017-8427-x},
	author = {Angelique Van Ombergen and Athena Demertzi and Elena Tomilovskaya and Ben Jeurissen and Jan Sijbers and Inessa B. Kozlovskaya and Paul M Parizel and Paul H Van de Heyning and Stefan Sunaert and Steven S L Laureys and Floris L Wuyts}
}
@article {1676,
	title = {Ergonomic design of an EEG headset using 3D anthropometry},
	journal = {Applied Ergonomics},
	volume = {58},
	year = {2017},
	month = {2017},
	pages = {128{\textendash}136},
	doi = {doi:10.1016/j.apergo.2016.06.002},
	author = {Daniel Lacko and Jochen Vleugels and Erik Fransen and Toon Huysmans and Guido De Bruyne and Marc M. Van Hulle and Jan Sijbers and Stijn Verwulgen}
}
@article {1766,
	title = { Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging},
	journal = {NeuroImage},
	volume = {146},
	year = {2017},
	pages = {789-803},
	doi = {10.1016/j.neuroimage.2016.09.067},
	author = {Hamaide, Julie and G. De Groof and Gwendolyn Van Steenkiste and Ben Jeurissen and Johan Van Audekerke and Maarten Naeyaert and Van Ruijssevelt, Lisbeth and Cornil, Charlotte and Jan Sijbers and Marleen Verhoye and Annemie Van Der Linden}
}
@inproceedings {1753,
	title = {Fast Reconstruction of CFRP X-ray Images based on a Neural Network Filtered Backprojection Approach},
	booktitle = {7th Conference on Industrial Computed Tomography},
	year = {2017},
	address = {Leuven, Belgium},
	url = {http://www.ndt.net/events/iCT2017/app/content/Extended_Abstract/63_Janssens_Rev4.pdf},
	author = {Eline Janssens and Sascha Senck and Christoph Heinzl and Johann Kastner and Jan De Beenhouwer and Jan Sijbers}
}
@conference {1768,
	title = {Fracture Patterns In Midshaft Clavicle Fracture},
	year = {2017},
	author = {Van Tongel, Alexander and Lieven De Wilde and Ken De Smet and Thomas Decock and Edward Van Herzele and Robin Van Den Broecke and Yasunori Shimamura and Jan Sijbers and Toon Huysmans}
}
@article {1802,
	title = {Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy},
	journal = {Remote Sensing},
	volume = {9},
	year = {2017},
	chapter = {266},
	author = {Birgen Haest and Jeroen Vanden Borre and Toon Spanhove and Guy Thoonen and Stephanie Delalieux and Kooistra, L. and C A M{\"u}cher and D Paelinckx and Paul Scheunders and Pieter Kempeneers}
}
@article {1762,
	title = {Intrinsic connectivity reduces in vestibular-related regions after first-time exposure to short-term gravitational alterations},
	journal = {Scientific Reports},
	volume = {7},
	year = {2017},
	doi = {10.1038/s41598-017-03170-5},
	author = {Angelique Van Ombergen and Floris L Wuyts and Ben Jeurissen and Jan Sijbers and Floris Vanhevel and Steven Jillings and Paul M Parizel and Stefan Sunaert and Paul H Van de Heyning and Vincent Dousset and Steven S L Laureys and Athena Demertzi}
}
@conference {1996,
	title = {Maximizing precision in PCASL MRI using an optimized sampling strategy},
	year = {2017},
	author = {Piet Bladt and Arnold Jan den Dekker and Clement, Patricia and Eric Achten and Jan Sijbers}
}
@article {2047,
	title = {Mobile imaging of an object using penetrating radiation},
	number = {WO/2017/178334},
	year = {2017},
	chapter = {PCT/EP2017/058270},
	author = {Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {1821,
	title = {Model-based reconstruction algorithms for dynamic X-ray CT},
	volume = {PhD in Sciences/Physics},
	year = {2017},
	type = {PhD thesis},
	author = {Vincent Van Nieuwenhove}
}
@article {1773,
	title = {MoVIT: A tomographic reconstruction framework for 4D-CT},
	journal = {Optics Express},
	volume = {25},
	year = {2017},
	pages = {19236-19250},
	abstract = {4D computed tomography (4D-CT) aims to visualise the temporal dynamics of a 3D sample with a sufficiently high temporal and spatial resolution.  Successive time frames are typically obtained by sequential scanning, followed by independent reconstruction of each 3D dataset. Such an approach requires a large number of projections for each scan to obtain images with sufficient quality (in terms of artefacts and SNR). Hence, there is a clear trade-off between the rotation speed of the gantry (i.e. time resolution) and the quality of the reconstructed images.
In this paper, the MotionVector-based Iterative Technique (MoVIT) is introduced which reconstructs a particular time frame by including the projections of neighbouring time frames as well. It is shown that such a  strategy improves the trade-off between the rotation speed and the SNR.
The framework is tested on both numerical simulations and on 4D X-ray CT datasets of polyurethane foam under compression.
Results show that reconstructions obtained with MoVIT have a significantly higher SNR compared to the SNR of conventional 4D reconstructions.},
	doi = {https://doi.org/10.1364/OE.25.019236},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jelle Vlassenbroeck and Mark Brennan and Jan Sijbers}
}
@article {1759,
	title = {Multisensor X-ray inspection of internal defects in horticultural products},
	journal = {Postharvest Biology and Technology},
	volume = {128},
	year = {2017},
	month = {June},
	pages = {33{\textendash}43},
	doi = {https://doi.org/10.1016/j.postharvbio.2017.02.002},
	author = {Mattias Van Dael and Pieter Verboven and Jelle Dhaene and Luc Van Hoorebeke and Jan Sijbers and Bart Nicolai}
}
@article {1775,
	title = {A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps},
	journal = {Signal Image and Video Processing},
	volume = {11},
	year = {2017},
	pages = { 913-920},
	author = {P V Sudeep and Palanisamy, P and Chandrasekharan Kesavadas and Jan Sijbers and Arnold Jan den Dekker and Jeny Rajan}
}
@conference {1997,
	title = {Optimal sampling strategy for pseudo-continuous arterial spin labeling MRI},
	year = {2017},
	author = {Piet Bladt and Arnold Jan den Dekker and Clement, Patricia and Eric Achten and Jan Sijbers}
}
@article {1722,
	title = {Partial Discreteness: a Novel Prior for Magnetic Resonance Image Reconstruction},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {36},
	year = {2017},
	pages = {1041 - 1053},
	doi = {10.1109/TMI.2016.2645122},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1774,
	title = {Product sizing with 3D anthropometry and k-medoids clustering},
	journal = {Computer-Aided Design},
	volume = {91},
	year = {2017},
	pages = {60-74},
	doi = {https://doi.org/10.1016/j.cad.2017.06.004},
	author = {Daniel Lacko and Toon Huysmans and Jochen Vleugels and Guido De Bruyne and Marc M. Van Hulle and Jan Sijbers and Stijn Verwulgen}
}
@inproceedings {1743,
	title = {Registration Based SIRT: A reconstruction algorithm for 4D CT},
	booktitle = {7th Conference on Industrial Computed Tomography},
	year = {2017},
	address = {Leuven, Belgium},
	abstract = {The goal of 4D computed tomography (4D CT) is to study the temporal deformation of a 3D sample with a sufficiently high temporal and spatial resolution. Conventionally, the sample is sequentially scanned, resulting in datasets of successive time frames. Each of these datasets is then independently reconstructed. This framework results in a trade-off between the temporal resolution and the signal-to-noise ratio (SNR) of the reconstructed images. The proposed registration based simultaneous iterative reconstruction technique (RBSIRT) allows shortening the acquisition time per time frame, leading to improved temporal resolution at comparable SNR. To this end, the algorithm estimates the deformation field between different time frames, which allows incorporating projections of other time frames into the reconstruction of a particular time frame. The technique was validated on numeric simulations and on a real dynamic experiment of a polyurethane foam sample. The reconstructions obtained with RBSIRT have a significantly higher SNR compared to the SNR of conventional 4D reconstructions.},
	url = {http://www.ndt.net/events/iCT2017/app/content/Paper/42_VanNieuwenhove.pdf},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jelle Vlassenbroeck and Maarten Moesen and Mark Brennan and Jan Sijbers}
}
@conference {1764,
	title = {Solving the Free Water Elimination Estimation Problem by Incorporating T2 Relaxation Properties},
	year = {2017},
	author = {Quinten Collier and Jelle Veraart and Arnold Jan den Dekker and Floris Vanhevel and Paul M Parizel and Jan Sijbers}
}
@conference {1818,
	title = {Statistically optimal separation of multi-component MR signals with a Majorize-Minimize approach: application to MWF estimation},
	year = {2017},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Piet Bladt and A. Cuyt and Jan Sijbers}
}
@conference {1826,
	title = {Super-resolution multi-PLD PCASL: a simulation study},
	volume = {30 (Suppl. 1)},
	number = {S396},
	year = {2017},
	publisher = {Magn Reson Mater Phy},
	abstract = {Cerebral blood flow (CBF) can be estimated non-invasively with arterial spin labeling (ASL). Multi-post-labeling-delay (PLD) pseudo-continuous ASL (PCASL) allows for accurate CBF estimation by sampling the dynamic perfusion signal at different PLDs and fitting a model to the perfusion data. Unfortunately, ASL difference images have a low SNR. Therefore, CBF estimation in multi-PLD PCASL is imprecise, unless a large number of images is acquired (long scan time) or spatial resolution is lowered significantly. It has been shown that model-based super-resolution reconstruction (SRR) techniques can improve the trade-off between SNR, spatial resolution and acquisition time. The results presented in this work show the promising potential of SRR ASL to outperform conventional ASL readout schemes in terms of achievable precision of HR perfusion measurements in a given acquisition time.},
	doi = {10.1007/s10334-017-0634-z},
	author = {Piet Bladt and Quinten Beirinckx and Gwendolyn Van Steenkiste and Ben Jeurissen and Eric Achten and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1668,
	title = {Super-resolution T1 estimation: quantitative high resolution T1 mapping from a set of low resolution T1 weighted images with different slice orientations},
	journal = {Magnetic Resonance in Medicine},
	volume = {77},
	year = {2017},
	pages = {1818{\textendash}1830},
	doi = {10.1002/mrm.26262},
	author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Floris Vanhevel and Paul M Parizel and Jan Sijbers}
}
@article {1706,
	title = {A unified Maximum Likelihood framework for simultaneous motion and T1 estimation in quantitative MR T1 mapping},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {36},
	year = {2017},
	pages = {433 - 446},
	doi = {10.1109/TMI.2016.2611653},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Gwendolyn Van Steenkiste and Ben Jeurissen and Floris Vanhevel and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@conference {1784,
	title = {A workflow to reconstruct grating-based X-ray phase contrast CT images: application to CFRP samples},
	year = {2017},
	pages = {139-140},
	address = {Z{\"u}rich, Switzerland},
	abstract = {Carbon fiber reinforced polymer (CFRP) is an extremely strong and lightweight plastic of which the strength depends on the distribution of its fibers. Fiber bundles can be visualized by means of phase contrast X-ray computed tomography (PCCT) based on grating-based interferometry (GBI). However, many steps are involved in the reconstruction of GBI-PCCT images. In this abstract, a workflow for the reconstruction of 3D CFRP phase contrast images based on GBI projection data is presented.},
	keywords = {Carbon fiber reinforced polymer, Image processing, Phase contrast, Tomography, X-rays},
	url = {https://indico.psi.ch/getFile.py/access?resId=1\&materialId=2\&confId=5055},
	author = {Jonathan Sanctorum and Eline Janssens and Arnold Jan den Dekker and Sascha Senck and Christoph Heinzl and Jan De Beenhouwer and Jan Sijbers}
}
@article {1644,
	title = {3D morphometric analysis of the human incudomallear complex using clinical cone-beam CT},
	journal = {Hearing research},
	volume = {340},
	year = {2016},
	pages = {79-88},
	abstract = {Human middle ears show large morphological variations. This could affect our perception of hearing and explain large variation in experimentally obtained transfer functions. Most morphological studies focus on capturing variation by using landmarks on cadaveric temporal bones. We present statistical shape analysis based on clinical cone beam CT (CBCT) scans of 100 patients. This allowed us to include surface information on the incudomallear (IM) complex (joint, ligaments and tendon not included) of 123 healthy ears with a scanning resolution of 150~μm and without a priori assumptions. Statistical shape modeling yields an average geometry for the IM complex and the variations present in the population with a high precision. Mean values, variation and correlations among anatomical features (length of manubrium, combined length of malleus head and neck, lengths of incus long and short process, enclosing angles, ossicular lever ratio, incudomallear angle, and principal moments of inertia) are reported and compared to results from the literature. Most variation is found in overall size and the angle between incus and malleus. The compact representation provided by statistical shape modeling is demonstrated and its benefits for surface modeling are discussed.},
	issn = {1878-5891},
	doi = {10.1016/j.heares.2016.01.014},
	author = {Joris Soons and Femke Danckaers and Keustermans, William and Toon Huysmans and Jan Sijbers and Casselman, Jan W and Joris J. J. Dirckx}
}
@proceedings {1905,
	title = {ACIVS 2016, Advanced Concepts for Intelligent Vision Systems},
	volume = {10016},
	year = {2016},
	author = {C Distante and J Blanc-Talon and Wilfried Philips and D Popescu and Paul Scheunders}
}
@article {VanAert:gq5005,
	title = {Advanced electron crystallography through model-based imaging},
	journal = {IUCrJ},
	volume = {3},
	number = {1},
	year = {2016},
	month = {Jan},
	abstract = {The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.},
	keywords = {experimental design, quantitative analysis, statistical parameter estimation, structure refinement, transmission electron microscopy},
	doi = {10.1107/S2052252515019727},
	url = {http://dx.doi.org/10.1107/S2052252515019727},
	author = {Sandra Van Aert and Annick De Backer and Martinez, Gerardo T. and Arnold Jan den Dekker and Dirk Van Dyck and Sara Bals and Van Tendeloo, Gustaaf}
}
@article {1778,
	title = {Automated quality control and selection },
	number = {PCT/EP2016/055718},
	year = {2016},
	chapter = {WO2016146703 A1},
	author = {Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jelle Dhaene and Luc Van Hoorebeke and Jan Sijbers}
}
@conference {1888,
	title = {Bayesian model-order selection in electron microscopy to detect atomic columns in noisy images},
	year = {2016},
	pages = {53},
	author = {J Fatermans and Sandra Van Aert and Arnold Jan den Dekker}
}
@conference {1643,
	title = {Building 3D Statistical Shape Models of Vegetables and Fruit},
	year = {2016},
	abstract = {Introduction
Statistical shape modeling is a promising approach to map out the variability of a population. By adapting the parameters of the shape model, a new, realistic surface can be obtained. In this work, the framework for surface registration and building a statistical shape model of fruit is described.

Method
The framework consists of two parts. First, a reference surface is registered to each fruit. Based on the correspondences that resulted from this surface registration, a statistical shape model is built. In the surface registration part, a reference surface is registered to a target surface, such that the geometric distance between those surfaces becomes minimal while maintaining correspondences. The second part of our framework consists of building a statistical shape model based on the correspondences that resulted from the surface registration (Fig. 1). The model is built by performing principal
components analysis on the corresponding points matrix of the population. In this model, the mean surface and the main shape modes are captured.
Parametrization of a surface is the task of defining a map between the surface and a simple parameter domain, such as a cylinder or sphere, so each fruit in the model can be described using basis functions, such as B-splines. This is a very compact representation and is useful in CAD and finite-element environments, so the models can be used for simulations.

Results
Experiments resulted in better correspondences than the current state-of-the-art. This means that our shape model is a good representation of the population and adapting the shape model parameters will lead to a realistic surface.

Applications
Possible applications of a statistical shape model of fruit are predicting the final size of the fruit, search for correlations between stages of growth, estimate the volume from a single view and evaluation of the effect of the fruit shape on airflow characteristics to obtain cooling uniformity.},
	author = {Femke Danckaers and Toon Huysmans and Jan Sijbers}
}
@conference {1694,
	title = {Building a statistical shape model of the interior and exterior of the bell pepper},
	volume = {28-30 November},
	year = {2016},
	address = {Vienna, Austria},
	author = {Femke Danckaers and Toon Huysmans and Seppe Rogge and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@article {1683,
	title = {Chronic exposure to haloperidol and olanzapine leads to common and divergent shape changes in the rat hippocampus in the absence of grey-matter volume loss},
	journal = {Psychological Medicine},
	volume = {46},
	year = {2016},
	pages = {3081-3093},
	doi = {10.1017/S0033291716001768},
	author = {William R Crum and Femke Danckaers and Toon Huysmans and Marie-Caroline Cotel and Sridhar Natesan and Michel M. Modo and Jan Sijbers and Steven C.R. Williams and Shitij Kapur and Anthony C. Vernon}
}
@inproceedings {1737,
	title = {Close range hyperspectral imaging for plant phenotyping},
	booktitle = {Hyperspectral Imaging and Applications Conference},
	year = {2016},
	month = {October/2016},
	address = {Coventry, UK},
	author = {Puneet Mishra and Mohd Shahrimie Mohd Asaari and Stien Mertens and Nathalie Wuyts and Stijn Dhondt and Paul Scheunders}
}
@conference {1728,
	title = {Combining 3D vision and X-ray radiography for internal quality inspection of foods},
	year = {2016},
	month = {28-30 November},
	address = {Austrian Economic Chamber, Vienna, Austria},
	author = {Mattias Van Dael and Femke Danckaers and Thomas De Schryver and Toon Huysmans and Pieter Verboven and Luc Van Hoorebeke and Jan Sijbers and Bart Nicolai}
}
@article {1584,
	title = {Cortical reorganization in an astronaut{\textquoteright}s brain after long-duration spaceflight},
	journal = {Brain Structure and Function},
	volume = {221},
	year = {2016},
	pages = {2873{\textendash}2876},
	doi = {10.1007/s00429-015-1054-3},
	author = {Athena Demertzi and Angelique Van Ombergen and Elena Tomilovskaya and Ben Jeurissen and Ekaterina V. Pechenkova and Carol Di Perri and Liudmila Litvinova and Enrico Amico and Alena Rumshiskaya and Ilya Rukavishnikov and Jan Sijbers and Valentin Sinitsyn and Inessa B. Kozlovskaya and Stefan Sunaert and Paul M Parizel and Paul H Van de Heyning and Steven S L Laureys and Floris L Wuyts}
}
@article {1763,
	title = {Denoising of diffusion MRI using random matrix theory},
	journal = {NeuroImage},
	volume = {142},
	year = {2016},
	pages = {384-396},
	doi = {10.1016/j.neuroimage.2016.08.016},
	author = {Jelle Veraart and Dmitry S. Novikov and Christiaens Daan and Ades-Aron, Benjamin and Jan Sijbers and Els Fieremans}
}
@article {1688,
	title = {Detecting and locating light atoms from high-resolution STEM images: the quest for a single optimal design Ultramicroscopy},
	journal = {Ultramicroscopy},
	volume = {170},
	year = {2016},
	pages = {128-138},
	doi = {http://dx.doi.org/10.1016/j.ultramic.2016.07.014},
	author = {Julie Gonnissen and Annick De Backer and Arnold Jan den Dekker and Jan Sijbers and Sandra Van Aert}
}
@article {1620,
	title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination},
	journal = {NeuroImage},
	volume = {125},
	year = {2016},
	pages = {363{\textendash}377},
	doi = {10.1016/j.neuroimage.2015.10.052},
	author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Maarten Naeyaert and Greetje Vanhoutte and Rafael  Delgado Y Palacios and Jelle Praet and Els Fieremans and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye}
}
@inproceedings {1652,
	title = {Discrete tomographic reconstruction from deliberately motion blurred X-ray projections},
	booktitle = {6th Conference on Industrial Computed Tomography},
	year = {2016},
	pages = {1-6},
	address = {Wels, Austria},
	author = {Wim Van Aarle and Jeroen Cant and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1619,
	title = {Dynamic flat field correction in X-ray computed tomography},
	booktitle = {Optimess conference},
	year = {2016},
	edition = {Antwerp},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1627,
	title = {A dynamic region estimation method for cerebral perfusion CT},
	booktitle = {6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS)},
	year = {2016},
	pages = {331-342},
	abstract = {In cerebral perfusion computed tomography (PCT), multiple scans of the brain are acquired after an intravenous contrast bolus injection. Therefore, radiation dose is a major issue. 
Recently, methods have been proposed that can reconstruct high quality dynamic (i.e., 4D) images, while keeping the radiation dose limited. These methods typically require an accurate estimate of the dynamic region inside the brain volume, i.e., the region containing tissue/vessels. Conventionally, the dynamic region is indicated manually.
In this work, a method for low-dose cerebral PCT is presented in which the dynamic region is estimated in an automatic way.
Simulation results on two PCT phantoms show that the dynamic region can be accurately estimated, even in a very low-dose regime, which is an important step towards more powerful reconstruction methods for low-dose cerebral PCT.
},
	author = {Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1696,
	title = {Evaluation of the thickness of hair layer from 3D scans and medical images},
	booktitle = {7th International Conference and Exhibition on 3D Body Scanning Technologies (3DBST)},
	year = {2016},
	edition = {Lugano, Switzerland, 30 November - 1 December},
	author = {Stijn Verwulgen and Jochen Vleugels and Daniel Lacko and Guido De Bruyne and Toon Huysmans}
}
@article {1701,
	title = {Fast and Flexible X-ray Tomography Using the ASTRA Toolbox},
	journal = {Optics Express},
	volume = {24},
	number = {22},
	year = {2016},
	pages = {25129-25147},
	doi = {10.1364/OE.24.025129},
	author = {Wim Van Aarle and Willem Jan Palenstijn and Jeroen Cant and Eline Janssens and Folkert Bleichrodt and Andrei Dabravolski and Jan De Beenhouwer and Kees Joost Batenburg and Jan Sijbers}
}
@article {1665,
	title = {Fast inline inspection by neural network based filtered backprojection: Application to apple inspection},
	journal = {Case Studies in Nondestructive Testing and Evaluation},
	volume = {6},
	year = {2016},
	pages = {14{\textendash}20},
	doi = {10.1016/j.csndt.2016.03.003},
	author = {Eline Janssens and Luis Filipe Alves Pereira and Jan De Beenhouwer and Ing Ren Tsang and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@inproceedings {1695,
	title = {Foot Abnormality Mapping using Statistical Shape Modelling},
	booktitle = {7th International Conference and Exhibition on 3D Body Scanning Technologies (3DBST)},
	year = {2016},
	pages = {70-79},
	edition = {Lugano, Switzerland, 30 November - 1 December},
	doi = {doi:10.15221/16.070},
	author = {Kristina Stankovi{\'c} and Femke Danckaers and Brian G Booth and Fien Burg and Saartje Duerinck and Jan Sijbers and Toon Huysmans}
}
@conference {Van_Steenkiste2016-fy,
	title = {High Resolution Diffusion Tensor Reconstruction from Simultaneous Multi-Slice Acquisitions in a Clinically Feasible Scan Time},
	year = {2016},
	pages = {2},
	author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Baete, Steven and Arnold Jan den Dekker and Dirk H J Poot and Boada, Fernando and Jan Sijbers}
}
@conference {1642,
	title = {In vivo high resolution diffusion tensor imaging in a clinically acceptable scan time by combining super resolution reconstruction with simultaneous multi-slice acquisition},
	volume = {8},
	number = {P-036},
	year = {2016},
	author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Steven Baete and Arnold Jan den Dekker and Dirk H J Poot and Fernando Boada and Jan Sijbers}
}
@article {1708,
	title = {In-line NDT with X-Ray CT combining sample rotation and translation},
	journal = {NDT \& E International},
	volume = {89},
	year = {2016},
	pages = {89{\textendash}98},
	doi = {10.1016/j.ndteint.2016.09.001},
	author = {Thomas De Schryver and Jelle Dhaene and Manuel Dierick and Boone, M.N. and Eline Janssens and Jan Sijbers and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Luc Van Hoorebeke}
}
@article {1664,
	title = {Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data},
	journal = {Journal of Synchrotron Radiation},
	volume = {23},
	year = {2016},
	pages = {842-849},
	doi = {10.1107/S1600577516005658},
	author = {Daan Pelt and Doga Gursoy and Willem Jan Palenstijn and Jan Sijbers and Francesco De Carlo and Kees Joost Batenburg}
}
@conference {1741,
	title = {Investigating lattice strain in Au nanodecahedrons},
	year = {2016},
	doi = {10.1002/9783527808465.EMC2016.5519},
	author = {Bart Goris and Jan De Beenhouwer and Annick De Backer and Daniele Zanaga and Kees Joost Batenburg and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and Sandra Van Aert and Jan Sijbers and Van Tendeloo, Gustaaf and Sara Bals}
}
@inproceedings {1667,
	title = {Investigation on Effect of scintillator thickness on Afterglow in Indirect X-ray Detectors},
	booktitle = {6th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2016)},
	year = {2016},
	abstract = {Solid-state scintillation detectors are widely used in modern multi-slice CT systems as well as synchrotron micro-tomography beamlines. Amongst other parameters, the performance of these detectors depends on the thickness of the scintillator. Thicker scintillators result in higher emission intensities, yet the resolution deteriorates as the thickness increases. To achieve a higher scan speed, thicker scintillators are more common. The thickness of scintillators however may influence the afterglow.  In this paper, we investigate the effect of scintillator thickness on the afterglow, using scintillating screens of two different materials (LAG:Ce and Gadox) and different thicknesses.  
Experimental results show that, apart from the scintillator material and excitation condition, the thickness of scintillator has a decisive role on the scintillator decay and particularly on the afterglow.
},
	keywords = {afterglow, flat-panel, image lag, scintillator thickness, synchrotron, x-ray detector},
	url = {http://www.ndt.net/article/ctc2016/papers/ICT2016_paper_id74.pdf},
	author = {Karim Zarei Zefreh and Jan De Beenhouwer and Federica Marone Welford and Jan Sijbers}
}
@conference {Kenney2016-ju,
	title = {Lateralisation of the arcuate fasciculus in psychosis \& the role in verbal learning \& auditory verbal hallucinations},
	volume = {26},
	year = {2016},
	pages = {S76{\textendash}S77},
	publisher = {Elsevier Science Bv},
	address = {Po Box 211, 1000 Ae Amsterdam, Netherlands},
	author = {Kenney, J and McInerney, S and McPhilemy, G and Najt, P and Scanlon, C and Arndt, S and Scherz, E and Byrne, F and Leemans, A and Ben Jeurissen and Donohoe, G and Hallahan, B and McDonald, C and Cannon, D}
}
@article {1703,
	title = {Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT},
	journal = {Medical Physics},
	volume = {43},
	year = {2016},
	pages = {6429-6438},
	doi = {10.1118/1.4967263},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Kees Joost Batenburg and Nico Buls and Jaf Vandemeulebroucke and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1736,
	title = {Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging},
	booktitle = {8th WHISPERS - Evolution in Remote Sensing},
	year = {2016},
	month = {August/2016},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Los Angeles, USA},
	author = {Mohd Shahrimie Mohd Asaari and Puneet Mishra and Stien Mertens and Stijn Dhondt and Nathalie Wuyts and Paul Scheunders}
}
@inproceedings {1653,
	title = {Multi-voxel algorithm for quantitative bi-exponential MRI T1 estimation},
	booktitle = {SPIE Medical Imaging},
	volume = {9784},
	year = {2016},
	pages = {978402},
	address = {San Diego, California, United States of America},
	abstract = {In this work, we propose a joint multi-voxel bi-exponential estimator (JMBE) for quantitative bi-exponential T1 estimation in magnetic resonance imaging, to account for partial volume effects and to yield more accurate results compared to single-voxel bi-exponential estimators (SBEs). Using a numerical brain phantom with voxels containing two tissues, the minimal signal-to-noise ratio (SNR) needed to estimate both T1 values with sufficient accuracy was investigated. Compared to the SBE, and for clinically achievable single-voxel SNRs, the JMBE yields accurate T1 estimates if four or more neighboring voxels are used in the joint estimation framework, in which case it is also efficient.},
	doi = {http://dx.doi.org/10.1117/12.2216831},
	author = {Piet Bladt and Gwendolyn Van Steenkiste and Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1647,
	title = {NOVIFAST: A fast non-linear least squares method for accurate and precise estimation of T1 from SPGR signals},
	year = {2016},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Marcus Bj{\"o}rk and Marleen Verhoye and Jan Sijbers}
}
@article {kenney2016p,
	title = {P. 3.033 Lateralisation of the arcuate fasciculus in psychosis \& the role in verbal learning \& auditory verbal hallucinations},
	journal = {European Neuropsychopharmacology},
	volume = {26},
	year = {2016},
	pages = {S76{\textendash}S77},
	author = {Kenney, J and McInerney, S and McPhilemy, G and Najt, P and Scanlon, C and Arndt, S and Scherz, E and Byrne, F and Alexander Leemans and Ben Jeurissen and G Donohoe and B Hallahan and C McDonald and D Cannon}
}
@inproceedings {1573,
	title = {Projection-based polygon estimation in X-ray computed tomography},
	booktitle = {6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS)},
	year = {2016},
	pages = {41-50},
	author = {Andrei Dabravolski and Jan De Beenhouwer and Jan Sijbers}
}
@conference {Collier2016-tu,
	title = {Robust DKI Parameter Estimation in Case of CSF Partial Volume Effects},
	year = {2016},
	pages = {1044},
	author = {Collier, Quinten and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@conference {1672,
	title = {Robust DKI parameter estimation in case of CSF partial volume effects},
	year = {2016},
	abstract = {Diffusion kurtosis imaging (DKI) suffers from partial volume effects caused by cerebrospinal fluid (CSF). We propose a DKI+CSF model combined with a framework to robustly estimate the DKI parameters. Since the estimation problem is ill-conditioned, a Bayesian estimation approach with a shrinkage prior is incorporated. Both simulation and real data experiments suggest that the use of this prior leads to a more accurate, precise and robust estimation of the DKI+CSF model parameters. Finally, we show that not correcting for the CSF compartment can lead to severe biases in the parameter estimations.},
	author = {Quinten Collier and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@conference {1671,
	title = {A robust framework for combined estimation of DKI and CSF partial volume fraction parameters},
	year = {2016},
	abstract = {Diffusion kurtosis imaging (DKI) suffers from partial volume effects caused by cerebrospinal fluid (CSF). We propose a DKI+CSF model combined with a framework to robustly estimate the DKI parameters. Since the estimation problem is ill-conditioned, a Bayesian estimation approach with a shrinkage prior is incorporated. Both simulation and real data experiments suggest that the use of this prior leads to a more accurate, precise and robust estimation of the DKI+CSF model parameters. Finally, we show that not correcting for the CSF compartment can lead to severe biases in the parameter estimations.},
	author = {Quinten Collier and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@article {1704,
	title = {StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images},
	journal = {Ultramicroscopy},
	volume = {171},
	year = {2016},
	pages = {104{\textendash}116},
	doi = {http://dx.doi.org/10.1016/j.ultramic.2016.08.018},
	author = {Annick De Backer and K.H.W. van den Bos and Wouter Van den Broek and Jan Sijbers and Sandra Van Aert}
}
@article {1536,
	title = {Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations},
	journal = {Magnetic Resonance in Medicine},
	volume = {75},
	year = {2016},
	pages = {181-195},
	doi = {10.1002/mrm.25597},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.25597/abstract},
	author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Jelle Veraart and Arnold Jan den Dekker and Paul M Parizel and Dirk H J Poot and Jan Sijbers}
}
@article {1690,
	title = {T1 relaxometry of crossing fibres in the human brain.},
	journal = {NeuroImage},
	year = {2016},
	month = {07/2016},
	abstract = {A comprehensive tract-based characterisation of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organisation within the voxel. Recently, a new experimental framework that combines inversion recovery and diffusion MRI, called inversion recovery diffusion tensor imaging (IR-DTI), was introduced and applied in an animal study. IR-DTI provides the ability to assign to each unique fibre population within a voxel a specific value of the longitudinal relaxation time, T1, which is a proxy for myelin content. Here, we apply the IR-DTI approach to the human brain in vivo on 7 healthy subjects for the first time. We demonstrate that the approach is able to measure differential tract properties in crossing fibre areas, reflecting the different myelination of tracts. We also show that tract-specific T1 has less inter-subject variability compared to conventional T1 in areas of crossing fibres, suggesting increased specificity to distinct fibre populations. Finally we show in simulations that changes in myelination selectively affecting one fibre bundle in crossing fibre areas can potentially be detected earlier using IR-DTI.},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2016.07.037},
	author = {Silvia De Santis and Yaniv Assaf and Ben Jeurissen and Derek K. Jones and Roebroeck, Alard}
}
@conference {1613,
	title = {3D evaluation of clavicle fractures},
	year = {2015},
	author = {Van Tongel, Alexander and Toussaint,, Arnaud and Lieven De Wilde and Toon Huysmans}
}
@conference {1589,
	title = {A 4D CT reconstruction algorithm for fast liquid flow imaging},
	year = {2015},
	abstract = {  The study of fluid flow through solid matter by computed tomography (CT) imaging has a broad range of applications, ranging from oil extraction to scientific research on fluid dynamics. Current techniques are often limited by a low temporal/spatial resolution. In this talk, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flowing through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation of a particular voxel in the dynamic region is modeled by a piecewise constant function over time (i.e., the voxel consists of fluid or air). Experiments on simulation data and on a real neutron tomography dataset demonstrate that the proposed approach can significantly increase the temporal resolution in comparison to conventional algorithms.},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
@article {1570,
	title = {4D-CT reconstruction with unified spatial-temporal patch-based regularization},
	journal = { Inverse Problems and Imaging},
	volume = {9},
	year = {2015},
	pages = {447-467},
	doi = {10.3934/ipi.2015.9.447},
	author = {Kazantsev, Daniil and Thompson, William M. and Lionheart, William R. B. and Van Eyndhoven, Geert and Kaestner,  Anders P. and Katherine J Dobson and Withers, Philip J. and Lee, Peter D.}
}
@inproceedings {1592,
	title = {Affine deformation correction in cone beam Computed Tomography},
	booktitle = {Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2015},
	pages = {182-185},
	address = {Newport, Rhode Island, USA},
	abstract = {In Computed Tomography (CT), motion and deformation during the acquisition produce streaks and blurring, known as motion artefacts. In contrast to other deformation correction techniques, this work introduces an efficient algorithm to correct for global affine deformations directly on the cone beam projections. During an experiment, the exact deformation parameters are unknown. These parameters are estimated in the projection domain by minimizing a plane based raw data redundancy criterion. Simulations and experimental data show a reduction of motion artefacts in the reconstructed images.},
	url = {http://fully3d.org/proceedings.html},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Thomas De Schryver and Luc Van Hoorebeke and Jan Sijbers}
}
@article {1580,
	title = {The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography},
	journal = {Ultramicroscopy},
	volume = {157},
	year = {2015},
	pages = {35{\textendash}47},
	doi = {10.1016/j.ultramic.2015.05.002},
	author = {Wim Van Aarle and Willem Jan Palenstijn and Jan De Beenhouwer and Thomas Altantzis and Sara Bals and Kees Joost Batenburg and Jan Sijbers}
}
@article {1582,
	title = {Building a Statistical Shape Model of the Apple from Corresponded Surfaces},
	journal = {Chemical Engineering Transactions},
	volume = {44},
	year = {2015},
	pages = {49-54},
	address = {Milano, Italy},
	abstract = {In this paper, a method for building a 3D statistical shape model of the apple is described. The framework consists of two parts. First, a reference surface is registered to each apple surface, derived from 3D CT scans of apples, of the population to obtain meaningful correspondences between the shapes. In the second part, the corresponded surfaces are used to build a statistical shape model from the population of apples. This model maps out the variability within the population and by adapting the shape model parameters, new, realistic surfaces can be obtained. By parameterizing the surface, an apple can be described with a compact set of basis functions, which has applications in surface fitting description, recognition, or meshing, e.g. for storage simulation. The constructed apple shape model is tested on performance and has proven to be a good representation of the population and can be used in many applications.},
	doi = { DOI:10.3303/CET1544009},
	author = {Femke Danckaers and Toon Huysmans and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@conference {1624,
	title = {CSF partial volume modeling in diffusion kurtosis imaging: a comparative parameter estimation study},
	year = {2015},
	month = {11/2015},
	doi = {10.3389/conf.fninf.2015.19.00039},
	url = {http://www.frontiersin.org/myfrontiers/events/abstractdetails.aspx?abs_doi=10.3389/conf.fninf.2015.19.00039},
	author = {Quinten Collier and Jelle Veraart and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@article {1604,
	title = {Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?},
	journal = {Journal of Alzheimer{\textquoteright}s Disease},
	volume = {48},
	number = {4},
	year = {2015},
	pages = {937-948},
	doi = {10.3233/JAD-150253},
	author = {Hanna Struyfs and Wim Van Hecke and Jelle Veraart and Jan Sijbers and Sylvie Slaets and Maya De Belder and Laura Wuyts and Benjamin Peters and Kristel Sleegers and Caroline Robberecht and Van Broeckhoven, Christine and Frank De Belder and Paul M Parizel and Sebastiaan Engelborghs}
}
@conference {1594,
	title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination},
	volume = {23},
	number = {4332},
	year = {2015},
	author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Jelle Praet and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye}
}
@article {1615,
	title = {Dynamic intensity normalization using eigen flat fields in X-ray imaging},
	journal = {Optics Express},
	volume = {23},
	year = {2015},
	pages = {27975-27989},
	abstract = {In X-ray imaging, it is common practice to normalize the acquired projection data with averaged flat fields taken prior to the scan. Unfortunately, due to source instabilities, vibrating beamline components such as the monochromator, time varying detector properties, or other confounding factors, flat fields are often far from stationary, resulting in significant systematic errors in intensity normalization. In this work, a simple and efficient method is proposed to account for dynamically varying flat fields. Through principal component analysis of a set of flat fields, eigen flat fields are computed. A linear combination of the most important eigen flat fields is then used to individually normalize each X-ray projection. Experiments show that the proposed dynamic flat field correction leads to a substantial reduction of systematic errors in projection intensity normalization compared to conventional flat field correction. },
	doi = {10.1364/OE.23.027975},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Francesco De Carlo and Lucia Mancini and Federica Marone and Jan Sijbers}
}
@article {1579,
	title = {Employing temporal self-similarity across the entire time domain in computed tomography reconstruction},
	journal = {Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences},
	volume = {373},
	number = {2043},
	year = {2015},
	publisher = {The Royal Society},
	abstract = {There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques.},
	isbn = {1471-2962},
	issn = {1364-503X},
	doi = {10.1098/rsta.2014.0389},
	author = {Kazantsev, Daniil and Van Eyndhoven, Geert and Lionheart, William R. B. and Withers, Philip J. and Katherine J Dobson and McDonald, S. A. and Atwood, R and Lee, Peter D.}
}
@inproceedings {1621,
	title = {Evaluation of 3D Body Shape Predictions Based on Features},
	booktitle = {6th International Conference on 3D Body Scanning Technologies},
	year = {2015},
	pages = {258-265},
	address = {Lugano, Switserland},
	abstract = {The human body comes in many sizes and shapes. For design purposes, it is useful to be able to quickly simulate a virtual mannequin of a customer. A statistical shape model can be used for this purpose, because it describes the main variations of body shape inside the model{\textquoteright}s population. From this model, the specific features of each person in the population are known. Therefore, a mapping between the shape model parameters and specific features can be calculated, which allows adjusting the body shape, in an intuitive way. In this work, we have investigated how accurate a body shape can be predicted based on a set of features and which features are most suitable for this purpose. Height, weight, and hip circumference appeared to be the most suitable features to accurately predict the body shape.},
	keywords = {body features, shape prediction},
	doi = {10.15221/15.258},
	author = {Femke Danckaers and Toon Huysmans and Daniel Lacko and Jan Sijbers}
}
@article {1517,
	title = {Evaluation of an anthropometric shape model of the human scalp},
	journal = {Applied Ergonomics},
	volume = {48},
	year = {2015},
	pages = {70-85},
	doi = {10.1016/j.apergo.2014.11.008},
	author = {Daniel Lacko and Toon Huysmans and Paul M Parizel and Guido De Bruyne and Stijn Verwulgen and Marc M. Van Hulle and Jan Sijbers}
}
@conference {1618,
	title = {A fast 4D CT reconstruction algorithm for affine deforming objects},
	year = {2015},
	edition = {Helsinki},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@article {1593,
	title = {Fast Fourier-based phase unwrapping on the graphics processing unit in real-time imaging applications},
	journal = {Journal of Imaging},
	volume = {1},
	year = {2015},
	pages = {31-44},
	doi = {doi:10.3390/jimaging1010031 },
	author = {Sam Van der Jeught and Jan Sijbers and Joris J. J. Dirckx}
}
@article {1591,
	title = {Fast Neural Network Based X-Ray Tomography of Fruit on a Conveyor Belt},
	journal = {Chemical Engineering Transactions},
	volume = {44},
	year = {2015},
	pages = {181-186},
	address = {Milano, Italy},
	doi = {10.3303/CET1544031},
	author = {Eline Janssens and Daan Pelt and Jan De Beenhouwer and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@conference {Van_Ombergen2015-nk,
	title = {A first insight in regional brain changes after parabolic flight: a voxel-based morphometry study},
	year = {2015},
	pages = {1258},
	author = {Angelique Van Ombergen and Ben Jeurissen and Floris Vanhevel and Loeckx, Dirk and Dousset, Vincent and Paul M Parizel and Floris L Wuyts}
}
@conference {1633,
	title = {High resolution diffusion tensor imaging in a clinically feasible scan time},
	year = {2015},
	doi = {10.3389/conf.fninf.2015.19.00016},
	author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Steven Baete and Arnold Jan den Dekker and Dirk H J Poot and Fernando Boada and Jan Sijbers}
}
@inproceedings {1548,
	title = {High resolution T1 estimation from multiple low resolution magnetic resonance images},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI): From nano to macro},
	volume = {12},
	year = {2015},
	pages = {1036-1039},
	doi = {10.1109/ISBI.2015.7164048},
	author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1661,
	title = {Inversion Recovery DTI In Vivo at 7T in the Human Brain},
	year = {2015},
	pages = {567},
	address = {Toronto, Ontario, Canada},
	author = {Silvia De Santis and Ben Jeurissen and Derek K. Jones and Yaniv Assaf and Alard Roebroek}
}
@article {1606,
	title = {An iterative CT reconstruction algorithm for fast fluid flow imaging},
	journal = {IEEE Transactions on Image Processing},
	volume = {24},
	year = {2015},
	pages = {4446-4458},
	abstract = {The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique.

In this paper, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary.

Quantitative and qualitative results on different simulation experiments and a real neutron tomography dataset show that, in comparison state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, temporal resolution can be substantially increased and thus fluid flow experiments with faster dynamics can be performed.},
	issn = {1057-7149},
	doi = {10.1109/TIP.2015.2466113},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
@article {1492,
	title = {Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters},
	journal = {Magnetic Resonance in Medicine},
	volume = {73},
	year = {2015},
	pages = {2174{\textendash}2184},
	abstract = {Purpose: Diffusion-weighted magnetic resonance imaging suffers from physiological noise, such as artifacts caused by motion or system instabilities. Therefore, there is a need for robust diffusion parameter estimation techniques. In the past, several techniques have been proposed, including RESTORE and iRESTORE. However, these techniques are based on nonlinear estimators and are consequently computationally intensive.
Method: In this work, we present a new, robust, iteratively reweighted linear least squares (IRLLS) estimator. IRLLS performs a voxel-wise identification of outliers in diffusion-weighted magnetic resonance images, where it exploits the natural skewness of the data distribution to become more sensitive to both signal hyperintensities and signal dropouts. 
Results: Both simulations and real data experiments were conducted to compare IRLLS with other state-of-the-art techniques. While IRLLS showed no significant loss in accuracy or precision, it proved to be substantially faster than both RESTORE and iRESTORE. In addition, IRLLS proved to be even more robust when considering the overestimation of the noise level or when the signal-to-noise ratio is low. 
Conclusion: The substantially shortened calculation time in combination with the increased robustness and accuracy, make IRLLS a practical and reliable alternative to current state-of-theart
techniques for the robust estimation of diffusion-weighted magnetic resonance parameters.},
	keywords = {diffusion tensor imaging, MRI, outlier detection, robust, weighted linear least squares},
	doi = {10.1002/mrm.25351},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1611,
	title = {Measuring Lattice Strain in Three Dimensions through Electron Microscopy},
	journal = {Nano Letters},
	volume = {15},
	year = {2015},
	pages = {6996{\textendash}7001},
	doi = {10.1021/acs.nanolett.5b03008},
	author = {Bart Goris and Jan De Beenhouwer and Annick De Backer and Daniele Zanaga and Kees Joost Batenburg and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and Sandra Van Aert and Sara Bals and Jan Sijbers and Van Tendeloo, Gustaaf}
}
@inproceedings {1576,
	title = {Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt},
	booktitle = {IEEE International Conference on Image Processing},
	year = {2015},
	month = {Sept 21-27},
	pages = {917-921},
	doi = {10.1109/ICIP.2015.7350933},
	author = {Eline Janssens and Jan De Beenhouwer and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@mastersthesis {1782,
	title = {Optical techniques for real-time morphology measurement of the tympanic membrane},
	year = {2015},
	type = {PhD thesis},
	author = {Sam Van der Jeught}
}
@conference {1561,
	title = {Partial discreteness: a new type of prior knowledge for MRI reconstruction},
	volume = {23},
	year = {2015},
	pages = {3417},
	author = {Gabriel Ramos-Llord{\'e}n and Segers, Hilde and Willem Jan Palenstijn and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {7351081,
	title = {Partially discrete magnetic resonance tomography},
	booktitle = {2015 IEEE International Conference on Image Processing (ICIP)},
	year = {2015},
	month = {Sept},
	pages = {1653-1657},
	keywords = {Bayes methods, Bayesian segmentation, Bayesian segmentation regularization, biomedical MRI, Breast, breast implant MR images, computerised tomography, Discrete tomography, image reconstruction, image representation, image segmentation, Implants, medical image processing, MR angiography images, MR image reconstruction, MRI, partially discrete magnetic resonance tomography, reconstruction, Tomography, TV},
	doi = {10.1109/ICIP.2015.7351081},
	author = {Gabriel Ramos-Llord{\'e}n and Segers, Hilde and Willem Jan Palenstijn and Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {VLEUGELS2015,
	title = {Physical Evaluation of an Anthropometric Shape Model of the Human Scalp},
	booktitle = {Proceedings of the 6th International Conference on 3D Body Scanning Technologies, Lugano, Switzerland, 27-28 October},
	year = {2015},
	month = {oct},
	publisher = {Hometrica Consulting},
	organization = {Hometrica Consulting},
	doi = {10.15221/15.161},
	url = {http://dx.doi.org/10.15221/15.161},
	author = {Jochen Vleugels and Daniel Lacko and Guido De Bruyne and Toon Huysmans and Stijn Verwulgen}
}
@conference {1537,
	title = {Simultaneous group-wise rigid registration and T1 ML estimation for T1 mapping},
	volume = {23},
	year = {2015},
	pages = {447},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Gwendolyn Van Steenkiste and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@conference {1537,
	title = {Simultaneous group-wise rigid registration and T1 ML estimation for T1 mapping},
	year = {2015},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Gwendolyn Van Steenkiste and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@inproceedings {7351386,
	title = {Simultaneous motion correction and T1 estimation in quantitative T1 mapping: An ML restoration approach},
	booktitle = {2015 IEEE International Conference on Image Processing (ICIP)},
	year = {2015},
	month = {Sept},
	pages = {3160-3164},
	keywords = {alignment, Approximation methods, biomedical MRI, image restoration, interpolation effect, Magnetic Resonance Imaging, maximum likelihood approach, maximum likelihood estimation, medical image processing, ML approach, ML restoration approach, motion estimation, motion model parameters, quantitative T1 mapping, registration, relaxometry, Rician channels, Signal to noise ratio, simultaneous motion correction, Standards, T1 estimation, T1 mapping, T1-weighted images, tissue spin-lattice relaxation time, voxel-wise estimation},
	doi = {10.1109/ICIP.2015.7351386},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Gwendolyn Van Steenkiste and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@inproceedings {2043,
	title = {SPIE ProceedingsEnergy calibration of photon counting detectors using x-ray tube potential as a reference for material decomposition applications},
	booktitle = {SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging},
	volume = {9412},
	year = {2015},
	pages = {941214},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Orlando, Florida, United States},
	doi = {10.1117/12.2082979},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2082979},
	author = {Das, Mini and Kandel, Bigyan and Park, Chan Soo and Zhihua Liang},
	editor = {Hoeschen, Christoph and Kontos, Despina and Flohr, Thomas G.}
}
@inproceedings {2044,
	title = {SPIE ProceedingsSingle-step, quantitative x-ray differential phase contrast imaging using spectral detection in a coded aperture setup},
	booktitle = {SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging},
	volume = {9412},
	year = {2015},
	pages = {941252},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Orlando, Florida, United States},
	doi = {10.1117/12.2082977},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2082977},
	author = {Das, Mini and Zhihua Liang},
	editor = {Hoeschen, Christoph and Kontos, Despina and Flohr, Thomas G.}
}
@inproceedings {2042,
	title = {SPIE ProceedingsTowards using eye-tracking data to develop visual-search observers for x-ray breast imaging},
	booktitle = {SPIE Medical ImagingMedical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment},
	volume = {9416},
	year = {2015},
	pages = {94160V},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Orlando, Florida, United States},
	doi = {10.1117/12.2082978},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2082978},
	author = {Jiang, Zhengqiang and Zhihua Liang and Das, Mini and Gifford, Howard C.},
	editor = {Mello-Thoms, Claudia R. and Kupinski, Matthew A.}
}
@conference {1605,
	title = {Statistical shape modeling of the incudomalleolar complex using micro-CT and clinical cone-beam CT},
	year = {2015},
	month = {July},
	address = {Aalborg, Denmark},
	abstract = {Introduction: A large variation in material properties and geometry exists in the human temporal bone. These variations can affect hearing and middle ear sound transmission. Middle ear computer (finite element, FE) models are successfully used to predict sound transmission and its dependence on material properties. The model geometry, however, is mostly based on data of a single sample. Here we use statistical shape models (SSM) to characterize the natural anatomical variations present in the incudomalleolar (IM) complex of humans. SSM can later be used in FE models to study the effect of geometry on sound transmission, or parameters can be fitted to clinical CT data to obtain a patient-specific computer model.

Methods and Materials: In this study we combine data of high resolution micro-CT scans (uCT, 20 um resolution) of 6 human cadaveric temporal bones and clinical cone-beam CT scans (CBCT, 150 um resolution) of 100 patients. First, a dense correspondence between the uCT samples is obtained by pair-wise elasticity modulated registration of a reference sample to each of the remaining samples. A SSM is built from these corresponded scans using principal component analysis (PCA), describing the average shape and the main variations of the middle ear within the uCT population. Next this SSM is fitted to clinical CBCT data by elastic registration with the SSM as shape prior.

Results and conclusions: We will obtain an average geometrical model for malleus, incus and IM complex and characterize the deviations present in the patient population. We will do this by reporting natural variation of size and thickness of malleus head, neck and manubrium, the long and short process of the incus and relative angles in the IM complex.},
	author = {Joris Soons and Femke Danckaers and Toon Huysmans and Jan Sijbers and Jan W. Casselamn and Joris J. J. Dirckx}
}
@conference {1596,
	title = {Super-resolution T1 mapping: a simulation study},
	volume = {23},
	year = {2015},
	pages = {1679},
	author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1544,
	title = {Theoretical study of the free water elimination model},
	year = {2015},
	pages = {78},
	abstract = {Partial volume effects caused by cerebrospinal fluid are an important issue in diffusion MRI. In this work, we study the free water elimination model by analyzing the Cram{\'e}r-Rao lower bound (CRLB) of its parameters. We show that through optimizing the acquisition protocol by minimizing the trace of the CRLB, a significant gain in the precision of the parameter estimation can be achieved. Moreover, further analysis indicates that regularization and/or constraints are necessary for parameter estimation from voxels with large CSF fractions and/or low FA values. These theoretical findings are confirmed by both simulation and real data experiments.},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {Collier2015-pa,
	title = {Theoretical study of the free water elimination model},
	volume = {15},
	year = {2015},
	pages = {2757},
	author = {Collier, Quinten and Veraart, Jelle and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1545,
	title = {Theoretical study of the free water elimination model},
	volume = {23},
	year = {2015},
	pages = {2757},
	abstract = {Partial volume effects caused by cerebrospinal fluid are an important issue in diffusion MRI. In this work, we study the free water elimination model by analyzing the Cram{\'e}r-Rao lower bound (CRLB) of its parameters. We show that through optimizing the acquisition protocol by minimizing the trace of the CRLB, a significant gain in the precision of the parameter estimation can be achieved. Moreover, further analysis indicates that regularization and/or constraints are necessary for parameter estimation from voxels with large CSF fractions and/or low FA values. These theoretical findings are confirmed by both simulation and real data experiments.},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1662,
	title = {Time to Move On: An FOD-Based DEC Map to Replace DTI{\textquoteright}s Trademark DEC FA},
	year = {2015},
	pages = {1027},
	author = {Thijs Dhollander and Robert Elton Smith and Jacques-Donald Tournier and Ben Jeurissen and Alan Connelly}
}
@article {1998,
	title = {Tomography for in-line product inspection},
	number = {EP3106863A1},
	year = {2015},
	chapter = {EP3106863A1},
	author = {Thomas De Schryver and Manuel Dierick and Luc Van Hoorebeke and Pieter Verboven and Mattias Van Dael and Jan Sijbers}
}
@mastersthesis {1632,
	title = {Towards In Loco X-ray Computed Tomography},
	year = {2015},
	month = {12/2015},
	type = {PhD thesis},
	author = {Andrei Dabravolski}
}
@article {1424,
	title = {Adaptive zooming in X-ray computed tomography},
	journal = {Journal of X-Ray Science and Technology},
	volume = {22},
	number = {1},
	year = {2014},
	pages = {77-89},
	keywords = {Acquisition geometry, adaptive zooming, computed tomography, prior information},
	doi = {10.3233/XST-130410},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1471,
	title = {Aligning Projection Images from Binary Volumes},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {1-22},
	doi = {10.3233/FI-2014-1090},
	author = {Folkert Bleichrodt and Jan De Beenhouwer and Jan Sijbers and Kees Joost Batenburg}
}
@conference {1487,
	title = {An Anthropometric Shape Model for the Design of Sports Helmets},
	year = {2014},
	author = {Daniel Lacko and Toon Huysmans and Annelies Claeskens and Stijn Verwulgen and Peter Aerts and Jan Sijbers and Guido De Bruyne}
}
@inproceedings {1501,
	title = {Anthropometrics 2.0: Enrichment of Classical Anthropometry through Multidisciplinary Collaboration},
	booktitle = {6th International Conference on Engineering \& Product Design Education.},
	year = {2014},
	author = {Stijn Verwulgen and Daniel Lacko and Guido De Bruyne and Femke Danckaers and Naomi Christis and Jan Sijbers and Toon Huysmans}
}
@article {2045,
	title = {Approximated transport-of-intensity equation for coded-aperture x-ray phase-contrast imaging},
	journal = {Optics Letters},
	volume = {39},
	year = {2014},
	month = {Jan-01-2014},
	pages = {5395},
	issn = {0146-9592},
	doi = {10.1364/OL.39.005395},
	url = {https://www.osapublishing.org/abstract.cfm?URI=ol-39-18-5395https://www.osapublishing.org/viewmedia.cfm?URI=ol-39-18-5395\&seq=0},
	author = {Das, Mini and Zhihua Liang}
}
@inproceedings {1453,
	title = {Automated Social behaviour Recognition At Low Resolution},
	booktitle = {22nd IEEE - International Conference of Pattern Recognition (ICPR)},
	year = {2014},
	author = {Tanmay Nath and G.Liu and Barbara Weyn and Bassem Hassan and Steve De Backer and Paul Scheunders}
}
@inproceedings {1533,
	title = {Automated Social behaviour Recognition At Low Resolution},
	booktitle = {ICPR14, International Conference on Pattern Recognition, Stockholm, Sweden},
	year = {2014},
	author = {Tanmay, Nath and G. Liu and Bassem Hassan and Barbara Weyn and Steve De Backer and Paul Scheunders}
}
@conference {1474,
	title = {Brain Tissue Types Resolved Using Spherical Deconvolution of Multi-Shell Diffusion MRI Data},
	year = {2014},
	month = {May},
	pages = {973},
	address = {Milan, Italy},
	author = {Ben Jeurissen and Jacques-Donald Tournier and Thijs Dhollander and Alan Connelly and Jan Sijbers}
}
@article {1504,
	title = {Combined Estimation of Affine Movement and Reconstruction in  Tomography},
	year = {2014},
	publisher = {3D Materials Science Conference},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@conference {1503,
	title = {Compensation of affine deformations in fan and cone beam projections},
	year = {2014},
	pages = {187-189},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1500,
	title = {Conveyor belt X-ray CT using Domain Constrained Discrete Tomography},
	booktitle = {Sibgrapi conference on Graphics, Patterns and Images},
	year = {2014},
	pages = {290 - 297},
	doi = {10.1109/SIBGRAPI.2014.21},
	author = {Luis Filipe Alves Pereira and Andrei Dabravolski and Ing Ren Tsang and George D C Cavalcanti and Jan Sijbers}
}
@inproceedings {1455,
	title = {Correspondence Preserving Elastic Surface Registration with Shape Model Prior},
	booktitle = {International Conference of Pattern Recognition},
	volume = {22},
	year = {2014},
	pages = {2143-2148},
	abstract = {In this paper, we describe a framework for surface
registration. The framework consists of a combination of rigid
registration, elasticity modulated registration and the use of a
shape model prior. The main goal in this paper is to mini-
mize the geometric surface registration error while maintain-
ing correspondences. Experiments show improved geometric fit,
correspondence, and timing compared to the current state of
the art. Possible applications of the framework are construction
of correspondences for shape models, reconstruction of missing
parts, and artifact reduction.},
	doi = {10.1109/ICPR.2014.373},
	author = {Femke Danckaers and Toon Huysmans and Daniel Lacko and A. Ledda and Stijn Verwulgen and Van Dongen, Stefan and Jan Sijbers}
}
@article {1476,
	title = {Data distributions in magnetic resonance images: a review},
	journal = {Physica Medica},
	volume = {30},
	year = {2014},
	pages = {725{\textendash}741},
	doi = {http://dx.doi.org/10.1016/j.ejmp.2014.05.002},
	author = {Arnold Jan den Dekker and Jan Sijbers}
}
@article {1418,
	title = {Dynamic Angle Selection in X-ray Computed Tomography},
	journal = {Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms},
	volume = {324},
	year = {2014},
	pages = {17-24},
	keywords = {Angle selection, computed tomography, dynamic imaging, information gain},
	doi = {10.1016/j.nimb.2013.08.077},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1488,
	title = {Evaluation of prominence of straight plates and precontoured clavicle plates using automated plate-to-bone fitting},
	journal = {Acta Orthopaedica Belgica},
	volume = {80},
	year = {2014},
	pages = {301-308},
	author = {Van Tongel, Alexander and Toon Huysmans and Amit Bernat and Iwein Piepers and Jan Sijbers and Francis Van Glabbeek and Lieven De Wilde}
}
@conference {1486,
	title = {Influence of Correspondence Method on Statistical Model Based Shape Prediction},
	year = {2014},
	author = {Christophe Van Dijck and Wirix-Speetjens, Roel and Toon Huysmans and Femke Danckaers and Jan Sijbers and Vander Sloten, Jos}
}
@inproceedings {1485,
	title = {Influence of Correspondence Method on Statistical Model Based Shape Prediction},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2014},
	author = {Christophe Van Dijck and Wirix-Speetjens, Roel and Toon Huysmans and Femke Danckaers and Jan Sijbers and Vander Sloten, Jos}
}
@booklet {1538,
	title = {Joint motion correction and estimation for T1 mapping: proof of concept},
	howpublished = {Medical Imaging Summer School 2014, Favignana, Italy},
	year = {2014},
	author = {Gabriel Ramos-Llord{\'e}n and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1502,
	title = {A Multiresolution Approach to Discrete Tomography Using DART},
	journal = {PLoS ONE},
	volume = {9},
	year = {2014},
	doi = {10.1371/journal.pone.0106090},
	url = {http://www.plosone.org/article/info\%3Adoi\%2F10.1371\%2Fjournal.pone.0106090},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1457,
	title = {A multiresolution approach to the Discrete Algebraic Reconstruction Technique (DART)},
	year = {2014},
	month = {07/2014},
	keywords = {computed tomography, DART, Discrete tomography, prior information},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1494,
	title = {Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data},
	journal = {NeuroImage},
	volume = {103},
	year = {2014},
	pages = {411{\textendash}426},
	abstract = {Constrained spherical deconvolution (CSD) has become one of the most widely used methods to extract white matter (WM) fibre orientation information from diffusion-weighted MRI (DW-MRI) data, overcoming the crossing fibre limitations inherent in the diffusion tensor model. It is routinely used to obtain high quality fibre orientation distribution function (fODF) estimates and fibre tractograms and is increasingly used to obtain apparent fibre density (AFD) measures. Unfortunately, CSD typically only supports data acquired on a single shell in q-space. With multi-shell data becoming more and more prevalent, there is a growing need for CSD to fully support such data. Furthermore, CSD can only provide high quality fODF estimates in voxels containing WM only. In voxels containing other tissue types such as grey matter (GM) and cerebrospinal fluid (CSF), the WM response function may no longer be appropriate and spherical deconvolution produces unreliable, noisy fODF estimates.

The aim of this study is to incorporate support for multi-shell data into the CSD approach as well as to exploit the unique b-value dependencies of the different tissue types to estimate a multi-tissue ODF. The resulting approach is dubbed multi-shell, multi-tissue CSD (MSMT-CSD) and is compared to the state-of-the-art single-shell, single-tissue CSD (SSST-CSD) approach. Using both simulations and real data, we show that MSMT-CSD can produce reliable WM/GM/CSF volume fraction maps, directly from the DW data, whereas SSST-CSD has a tendency to overestimate the WM volume in voxels containing GM and/or CSF. In addition, compared to SSST-CSD, MSMT-CSD can substantially increase the
precision of the fODF fibre orientations and reduce the presence of spurious fODF peaks in voxels containing GM and/or CSF. Both effects translate into more reliable AFD measures and tractography results with MSMT-CSD compared to SSST-CSD.},
	doi = {10.1016/j.neuroimage.2014.07.061},
	author = {Ben Jeurissen and Jacques-Donald Tournier and Thijs Dhollander and Alan Connelly and Jan Sijbers}
}
@article {1472,
	title = {Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor},
	journal = {Progress in Nuclear Energy},
	volume = {72},
	year = {2014},
	pages = {55-62},
	doi = {http://dx.doi.org/10.1016/j.pnucene.2013.11.001},
	author = {Hakon Kristian Jenssen and B.C. Oberlander and Jan De Beenhouwer and Jan Sijbers and M. Verwerft}
}
@article {1441,
	title = {A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test},
	journal = {Signal Processing},
	volume = {103},
	year = {2014},
	pages = {16-23},
	doi = {http://dx.doi.org/10.1016/j.sigpro.2013.12.018},
	author = {Jeny Rajan and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1497,
	title = {Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images},
	journal = {Applied Physics Letters},
	volume = {105},
	year = {2014},
	doi = {10.1063/1.4892884},
	author = {Julie Gonnissen and Annick De Backer and Arnold Jan den Dekker and G T Martinez and A. Rosenauer and Jan Sijbers and Sandra Van Aert}
}
@article {1480,
	title = {The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography},
	journal = {Computer Vision and Image Understanding},
	volume = {126},
	year = {2014},
	pages = {28-37},
	doi = {10.1016/j.cviu.2014.05.007},
	author = {Roelandts, Tom and Kees Joost Batenburg and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1546,
	title = {Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism.},
	journal = {NeuroImage},
	volume = {90},
	year = {2014},
	month = {2014 Apr 15},
	pages = {280-9},
	abstract = {BACKGROUND: The brain-derived neurotrophic factor (BDNF) val66met polymorphism is associated with altered activity dependent secretion of BDNF and a variable influence on brain morphology and cognition. Although a met-dose effect is generally assumed, to date the paucity of met-homozygotes have limited our understanding of the role of the met-allele on brain structure.

METHODS: To investigate this phenomenon, we recruited sixty normal healthy subjects, twenty in each genotypic group (val/val, val/met and met/met). Global and local morphology were assessed using voxel based morphometry and surface reconstruction methods. White matter organisation was also investigated using tract-based spatial statistics and constrained spherical deconvolution tractography.

RESULTS: Morphological analysis revealed an "inverted-U" shaped profile of cortical changes, with val/met heterozygotes most different relative to the two homozygous groups. These results were evident at a global and local level as well as in tractography analysis of white matter fibre bundles.

CONCLUSION: In contrast to our expectations, we found no evidence of a linear met-dose effect on brain structure, rather our results support the view that the heterozygotic BDNF val66met genotype is associated with cortical morphology that is more distinct from the BDNF val66met homozygotes. These results may prove significant in furthering our understanding of the role of the BDNF met-allele in disorders such as Alzheimer{\textquoteright}s disease and depression.},
	keywords = {Adolescent, Adult, Alleles, Brain, Brain-Derived Neurotrophic Factor, diffusion tensor imaging, Female, Genotype, Heterozygote, Homozygote, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Polymorphism, Single Nucleotide, Young Adult},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2013.12.050},
	author = {Forde, Natalie J and Ronan, Lisa and Suckling, John and Scanlon, Cathy and Neary, Simon and Holleran, Laurena and Alexander Leemans and Tait, Roger and Rua, Catarina and Fletcher, Paul C and Ben Jeurissen and Dodds, Chris M and Miller, Sam R and Bullmore, Edward T and Colm McDonald and Nathan, Pradeep J and Dara M. Cannon}
}
@inproceedings {1386,
	title = {Adaptive Zooming in X-ray Computed Tomography},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {5-8},
	address = {Ghent, Belgium},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1650,
	title = {An Alignment Method for Fan Beam Tomography},
	booktitle = {International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {103-107},
	author = {Folkert Bleichrodt and Jan De Beenhouwer and Jan Sijbers and Kees Joost Batenburg}
}
@article {1406,
	title = {Alveolar Nerve Unfolding Technique for Synoptic Analysis: Visualization and Quantification of Inferior Alveolar Nerve Tracings in Three-dimensional Cone-Beam Computed Tomography.},
	journal = {The Journal of craniofacial surgery},
	volume = {24},
	year = {2013},
	month = {2013 Jul},
	pages = {e374-7},
	abstract = {The aim of the technique presented here is to visualize the anatomical context of the inferior alveolar nerve (IAN) canal. For 2 cases, cone-beam computed tomography images of the mandible were obtained from patient files together with the manual preoperative IAN canal tracings. For both cases, similar to simulated panoramic images, a two-dimensional image is extracted from a three-dimensional cone-beam computed tomography image. Unlike panoramic images, the unfolding does not follow the general curvature of the mandible but follows the nerve tracing closely and places the traced nerve track on a horizontal central line. Because of the centering of the nerve tracing together with the nerve canal and its surroundings in a two-dimensional representation, the technique (ANUTSA [Alveolar Nerve Unfolding Technique for Synoptic Analysis]) allowed the first case to evidence the adjacency of root tips along the IAN, whereas in the second case the degree of penetration of the IAN by an implant is revealed. The global aspect of the representation through unfolding allowed for the detection of the anomalies and the IAN-penetrating lesion along the IAN canal at a glance.},
	issn = {1536-3732},
	doi = {10.1097/SCS.0b013e3182903013},
	author = {Jacquet, Wolfgang and Nyssen, Edgard and Sun, Yi and De Munter, Stephanie and Jan Sijbers and Politis, Constantinus}
}
@article {1377,
	title = {Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer{\textquoteright}s disease},
	journal = {Magnetic Resonance in Medicine},
	volume = {69},
	year = {2013},
	pages = {1115{\textendash}1121},
	doi = {10.1002/mrm.24680},
	author = {Greetje Vanhoutte and S. Pereson and Rafael  Delgado Y Palacios and Pieter-Jan Guns and B. Asselbergh and Jelle Veraart and Jan Sijbers and Marleen Verhoye and Van Broeckhoven, Christine and Annemie Van Der Linden}
}
@article {1361,
	title = {Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study.},
	journal = {European radiology},
	volume = {23},
	year = {2013},
	month = {2012 Jul 20},
	pages = {57-64},
	abstract = {OBJECTIVE: To evaluate the effect of monophasic combined oral contraceptive pill (COCP) and menstrual cycle phase in healthy young women on white matter (WM) organization using diffusion tensor imaging (DTI). METHODS: Thirty young women were included in the study; 15 women used COCP and 15 women had a natural cycle. All subjects underwent DTI magnetic resonance imaging during the follicular and luteal phase of their cycle, or in different COCP cycle phases. DTI parameters were obtained in different WM structures by performing diffusion tensor fibre tractography. Fractional anisotropy and mean diffusivity were calculated for different WM structures. Hormonal plasma concentrations were measured in peripheral venous blood samples and correlated with the DTI findings. RESULTS: We found a significant difference in mean diffusivity in the fornix between the COCP and the natural cycle group. Mean diffusivity values in the fornix were negatively correlated with luteinizing hormone and estradiol blood concentrations. CONCLUSION: An important part in the limbic system, the fornix, regulates emotional processes. Differences in diffusion parameters in the fornix may contribute to behavioural alternations related to COCP use. This finding also suggests that the use of oral contraceptives needs to be taken into account when designing DTI group studies. KEY POINTS: {\textbullet} Diffusion tensor MRI offers new insights into brain white matter microstructure. {\textbullet} The effects of oral hormonal contraception were examined in young women. {\textbullet} Diffusion tensor images and hormone blood concentrations were evaluated. {\textbullet} Women using hormonal contraception demonstrated higher mean diffusivity in the fornix. {\textbullet} These changes may contribute to behavioural alternations related to contraception use.},
	issn = {1432-1084},
	doi = {10.1007/s00330-012-2572-5},
	author = {De Bondt, Timo and Wim Van Hecke and Jelle Veraart and Alexander Leemans and Jan Sijbers and Stefan Sunaert and Jacquemyn, Yves and Paul M Parizel}
}
@inproceedings {1387,
	title = {Dynamic Angle Selection in X-ray Computed Tomography},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {27-30},
	address = {Ghent, Belgium},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1395,
	title = {Estimation of unknown structure parameters from high-resolution (S)TEM images: what are the limits?},
	journal = {Ultramicroscopy},
	volume = {134},
	year = {2013},
	pages = {34-43},
	doi = {http://dx.doi.org/10.1016/j.ultramic.2013.05.017},
	url = {http://www.sciencedirect.com/science/article/pii/S0304399113001368},
	author = {Arnold Jan den Dekker and Julie Gonnissen and Annick De Backer and Jan Sijbers and Sandra Van Aert}
}
@inproceedings {1439,
	title = {A New Nonlocal Maximum Likelihood Estimation Method for Denoising Magnetic Resonance Images},
	booktitle = {5th International Conference, PReMI 2013, Kolkata, India, December 10-14, 2013. Proceedings},
	volume = {8251},
	year = {2013},
	month = {2013},
	edition = {Lecture Notes in Computer Science},
	doi = {10.1007/978-3-642-45062-4_62},
	author = {Jeny Rajan and Arnold Jan den Dekker and Juntu, Jaber and Jan Sijbers}
}
@article {1470,
	title = {Regional gray matter volume differences and sex-hormone correlations as a function of menstrual cycle phase and hormonal contraceptives use.},
	journal = {Brain research},
	volume = {1530},
	year = {2013},
	month = {2013 Sep 12},
	pages = {22-31},
	abstract = {During the menstrual cycle, hormone-driven functional and morphological changes occur in the female brain. The influence of hormonal contraceptives on these changes has received only little attention in the medical literature. The purpose of our study is to measure regional gray matter volume changes as a function of the cycle phase and use of hormonal contraceptives, in relation to blood concentrations of sex hormones. We performed a prospective study in 30 healthy young women; 15 women had a natural menstrual cycle and 15 were using monophasic combined hormonal contraceptives. MRI examinations were acquired at 2 specific time-points in the cycle (follicular and luteal phase). MRI studies included a T1-weighted, isotropic, high-resolution 3-D gradient echo acquisition, for the purpose of performing voxel based morphometry. Peripheral venous blood samples were obtained to determine concentrations of luteinizing hormone (LH), follicle stimulating hormone (FSH), estradiol, and progesterone. We found a highly significant negative correlation of regional gray matter volume in the anterior cingulate cortex with estradiol concentrations. To the best of our knowledge, this result has not been described before, and was only present in the natural cycle group, not in women using hormonal contraceptives. The anterior cingulate cortex is involved in emotion processing and there is literature describing behavioral alternations with changing hormone levels. Our findings provide a structural, morphological basis to support these data. Therefore, we advise neuroscientists to take into account the menstrual cycle phase and use of hormonal contraceptives, in order to avoid obtaining heterogeneous data sets, leading to a significant loss of accuracy and precision.},
	issn = {1872-6240},
	doi = {10.1016/j.brainres.2013.07.034},
	author = {De Bondt, Timo and Jacquemyn, Y and Wim Van Hecke and Jan Sijbers and Stefan Sunaert and Paul M Parizel}
}
@article {1396,
	title = {Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI.},
	journal = {Psychopharmacology},
	volume = {227},
	year = {2013},
	month = {2013 Jun},
	pages = {479-91},
	abstract = {BACKGROUND: An effective NMDA antagonist imaging model may find key utility in advancing schizophrenia drug discovery research. We investigated effects of subchronic treatment with the NMDA antagonist memantine by using behavioural observation and multimodal MRI.

METHODS: Pharmacological MRI (phMRI) was used to map the neuroanatomical binding sites of memantine after acute and subchronic treatment. Resting state fMRI (rs-fMRI) and diffusion MRI were used to study the changes in functional connectivity (FC) and ultra-structural tissue integrity before and after subchronic memantine treatment. Further corroborating behavioural evidences were documented.

RESULTS: Dose-dependent phMRI activation was observed in the prelimbic cortex following acute doses of memantine. Subchronic treatment revealed significant effects in the hippocampus, cingulate, prelimbic and retrosplenial cortices. Decreases in FC amongst the hippocampal and frontal cortical structures (prelimbic, cingulate) were apparent through rs-fMRI investigation, indicating a loss of connectivity. Diffusion kurtosis MRI showed decreases in fractional anisotropy and mean diffusivity changes, suggesting ultra-structural changes in the hippocampus and cingulate cortex. Limited behavioural assessment suggested that memantine induced behavioural effects comparable to other NMDA antagonists as measured by locomotor hyperactivity and that the effects could be reversed by antipsychotic drugs.

CONCLUSION: Our findings substantiate the hypothesis that repeated NMDA receptor blockade with nonspecific, noncompetitive NMDA antagonists may lead to functional and ultra-structural alterations, particularly in the hippocampus and cingulate cortex. These changes may underlie the behavioural effects. Furthermore, the present findings underscore the utility and the translational potential of multimodal MR imaging and acute/subchronic memantine model in the search for novel disease-modifying treatments for schizophrenia.},
	issn = {1432-2072},
	doi = {10.1007/s00213-013-2966-3},
	author = {Sekar, S and Jonckers, E and Marleen Verhoye and Willems, R and Jelle Veraart and Johan Van Audekerke and Couto, J and Giugliano, M and Wuyts, K and Dedeurwaerdere, S and Jan Sijbers and Mackie, C and Ver Donck, L and Steckler, T and Annemie Van Der Linden}
}
@inproceedings {tanmay2013tracking,
	title = {Tracking for Quantifying Social Network of Drosophila Melanogaster},
	booktitle = {15th Computer Analysis of Images and Patterns (CAIP)},
	volume = {8048},
	year = {2013},
	pages = {539{\textendash}545},
	publisher = {Springer},
	organization = {Springer},
	author = {Tanmay Nath and Liu, Guangda and Barbara Weyn and Bassem Hassan and Steve De Backer and Paul Scheunders}
}
@article {1318,
	title = {A Bayesian Restoration Approach for Hyperspectral Images},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {50},
	year = {2012},
	pages = {3453-3462},
	author = {Y. Zhang and A. Duijster and Paul Scheunders}
}
@article {1304,
	title = {Diffusion kurtosis imaging in the grading of gliomas},
	journal = {Radiology},
	volume = {2},
	number = {263},
	year = {2012},
	pages = {492-501},
	doi = {10.1148/radiol.12110927},
	author = {Van Cauter, Sofie and Jelle Veraart and Jan Sijbers and Ron R Peeters and U. Himmelreich and S. Van Gool and Van Calenbergh, F. and De Vleeschouwer, S. and Wim Van Hecke and Stefan Sunaert}
}
@conference {1714,
	title = {A framework for markerless alignment with full 3D flexibility},
	year = {2012},
	author = {Jan De Beenhouwer and Willem Jan Palenstijn and Folkert Bleichrodt and Kees Joost Batenburg and Jan Sijbers}
}
@article {1349,
	title = {Identification and characterization of Huntington related pathology: an in vivo DKI imaging study},
	journal = {NeuroImage},
	volume = {63},
	year = {2012},
	month = {09/2012},
	pages = {653-662},
	doi = {http://dx.doi.org/10.1016/j.neuroimage.2012.06.032},
	author = {Ines Blockx and Marleen Verhoye and Johan Van Audekerke and Irene  Bergwerf and Jack X Kane and Rafael  Delgado Y Palacios and Jelle Veraart and Ben Jeurissen and Kerstin Raber and Von H{\"o}rsten, Stephan and Peter Ponsaerts and Jan Sijbers and Trygve B Leergaard and Annemie Van Der Linden}
}
@inproceedings {1356,
	title = {Imrpoving PLCA-based score-informed source separation with invertible constant-Q transform},
	booktitle = {EUSIPCO 2012, 20th European Signal Processing Conference, Bucharest, Romania, august 27-31 },
	year = {2012},
	pages = {2634-2638},
	author = {Joachim Ganseman and Paul Scheunders and S. Dixon}
}
@article {1309,
	title = {Microstructural changes observed with DKI in a transgenic Huntington rat model: Evidence for abnormal neurodevelopment.},
	journal = {NeuroImage},
	volume = {59},
	number = {2},
	year = {2012},
	month = {2012 Jan 16},
	pages = {957-67},
	abstract = {Huntington Disease (HD) is a fatal neurodegenerative disorder, caused by a mutation in the Huntington gene. Although HD is most often diagnosed in mid-life, the key to its clinical expression may be found during brain maturation. In the present work, we performed in vivo diffusion kurtosis imaging (DKI) in order to study brain microstructure alterations in developing transgenic HD rat pups. Several developing brain regions, relevant for HD pathology (caudate putamen, cortex, corpus callosum, external capsule and anterior commissure anterior), were examined at postnatal days 15 (P15) and 30 (P30), and DKI results were validated with histology. At P15, we observed higher mean (MD) and radial (RD) diffusivity values in the cortex of transgenic HD rat pups. In addition, at the age of P30, lower axial kurtosis (AK) values in the caudate putamen of transgenic HD pups were found. At the level of the external capsule, higher MD values at P15 but lower MD and AD values at P30 were detected. The observed DKI results have been confirmed by myelin basic protein immunohistochemistry, which revealed a reduced fiber staining as well as less ordered fibers in transgenic HD rat pups. These results indicate that neuronal development in young transgenic HD rat pups occurs differently compared to controls and that the presence of mutant huntingtin has an influence on postnatal brain development. In this context, various diffusivity parameters estimated by the DKI model are a powerful tool to assess changes in tissue microstructure and detect developmental changes in young transgenic HD rat pups.},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2011.08.062},
	author = {Ines Blockx and G. De Groof and Marleen Verhoye and Johan Van Audekerke and Kerstin Raber and Dirk H J Poot and Jan Sijbers and Osmand, Alexander P and Von H{\"o}rsten, Stephan and Annemie Van Der Linden}
}
@inbook {1257,
	title = {Wavelet-based Multi/Hyperspectral Image Restoration and Fusion},
	booktitle = {Signal and Image Processing for Remote Sensing},
	year = {2012},
	pages = {505-523},
	publisher = {Taylor and Francis},
	organization = {Taylor and Francis},
	chapter = {25},
	author = {Paul Scheunders and A. Duijster and Y. Zhang},
	editor = {C.H. Chen}
}
@inproceedings {WitteThoonenpscheundPizuricaPhilips2011,
	title = {Classification of multi-source images using color mathematical morphological profiles},
	booktitle = {Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International},
	year = {2011},
	pages = {3919 - 3922},
	address = {Vancouver, BC, Canada},
	abstract = {In the remote sensing domain data from many different sources are often available. Each of these data sources are characterized by their own sensor- and platform-specific properties, i.e. spectral range, or spatial and spectral resolution. In this paper we consider a low spatial, but high spectral resolution satellite image, together with its high spatial resolution RGB color image, e.g. obtained by UAV. Spatial features are extracted from the color image by combining the three color bands R, G and B, ordering these color vectors, and presenting color mathematical morphological profiles accordingly. This way the spatial information contained in the correlation between the different bands is completely taken into account and thus also totally preserved in the feature extraction. In a classification experiment these color morphological profiles are combined with the spectral features of the hyperspectral image, and we show that the spatial characterization of the color image is improved.},
	keywords = {Classification, Color, Morphological profiles, Multisource images, remote sensing},
	isbn = {978-1-4577-1003-2},
	issn = {2153-6996},
	doi = {10.1109/IGARSS.2011.6050088},
	url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=6050088\&isnumber=6048881},
	author = {Val{\'e}rie De Witte and Guy Thoonen and Paul Scheunders and Aleksandra Pizurica and Wilfried Philips}
}
@conference {Kudzinava_2011_WMSG,
	title = {Diffusion and kurtosis parameters in white matter of premature newborns},
	year = {2011},
	month = {August},
	pages = {21},
	address = {Reykjavik, Iceland},
	abstract = {Diffusion Tensor Imaging (DTI) is often used to study brain maturation processes and white matter (WM) injuries in premature newborns. However, DTI assumes that water diffusion in biological tissues is free. In reality, there is always structural hindrance in WM, which only increases with age due to myelination. Diffusional Kurtosis Imaging (DKI) relaxes the assumption of free diffusion and allows estimation of conventional diffusion parameters plus new kurtosis measures, which are related to tissue complexity. In this work, we present and discuss the first statistics of DKI parameters in WM of two prematurely born infants.},
	keywords = {anisotropy, diffusion, kurtosis, premature newborns, white matter},
	author = {Maryna Kudzinava and A. Plaisier and J. Dudink and Jan Sijbers}
}
@conference {R.jveraartG.H.mverhoyeP.jsijbersavdlinde2011,
	title = {Diffusion kurtosis abnormalities in pre-symptomatic (alpha)-synycleunopathy mouse model},
	year = {2011},
	month = {January},
	address = {Hoeven, The Netherlands},
	author = {Rafael  Delgado Y Palacios and Jelle Veraart and Greetje Vanhoutte and H. Schell and Marleen Verhoye and P. Kahle and Jan Sijbers and Annemie Van Der Linden}
}
@conference {1307,
	title = {Distortion correction of DKI data: affine approach},
	year = {2011},
	month = {December},
	abstract = {In this work, the performance of FMRIB{\textquoteright}s Linear Registration Tool (FLIRT) is evaluated with respect to motion and distortion correction of diffusion kurtosis imaging (DKI) data. FLIRT is tested on two DKI datasets heavily distorted by motion and eddy currents artefacts. Six different criteria are used for evaluation. Our results show that distortion correction using FLIRT substantially improves the original data. However, being an affine registration tool, FLIRT cannot cope with the amount of non-linear distortion present in DKI datasets. Hence, we conclude that, for correction of DKI data, non-linear registration techniques are more suitable.},
	keywords = {medical imaging},
	author = {Maryna Kudzinava and Alexander Leemans and Wilfried Philips and Daniele Perrone and Jan Aelterman and J. Dudink and Jan Sijbers}
}
@inproceedings {1942,
	title = {Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space},
	booktitle = {MICCAI 2011: Medical Image Computing and Computer-Assisted Intervention},
	year = {2011},
	pages = {166-173},
	author = {Thijs Dhollander and Jelle Veraart and Wim Van Hecke and F. Maes and Stefan Sunaert and Jan Sijbers and Paul Suetens}
}
@article {gvgompelSlambrouckDefrisejbatenbuMeyjsijbersNuyts2011,
	title = {Iterative correction of beam hardening artifacts in CT},
	journal = {Medical Physics},
	volume = {38},
	number = {1},
	year = {2011},
	month = {July},
	pages = {36-49},
	doi = {http://dx.doi.org/10.1118/1.3577758},
	author = {Gert Van Gompel and Van Slambrouck, Katrien and M. Defrise and Kees Joost Batenburg and Johan De Mey and Jan Sijbers and Johan Nuyts}
}
@article {R.AdriaanKimmverhoyedpootJoukeJ.HjsijbersOavdlinde2011,
	title = {Magnetic resonance imaging and spectroscopy reveal differential hippocampal changes in anhedonic and resilient subtypes of the chronic mild stress rat model},
	journal = {Biological psychiatry},
	volume = {70},
	number = {5},
	year = {2011},
	pages = {449-457},
	author = {Rafael  Delgado Y Palacios and Campo Adriaan and Henningsen Kim and Marleen Verhoye and Dirk H J Poot and Dijkstra Jouke and Johan Van Audekerke and H Benveniste and Jan Sijbers and O. Wiborg and Annemie Van Der Linden}
}
@inproceedings {jrajanmverhoyejsijbers2011,
	title = {A maximum likelihood estimation method for denoising magnitude MRI using restricted local neighborhood},
	booktitle = {SPIE Medical Imaging},
	volume = {7962},
	year = {2011},
	publisher = {SPIE},
	organization = {SPIE},
	author = {Jeny Rajan and Marleen Verhoye and Jan Sijbers},
	editor = {B.M. Dawant and D.R. Haynor}
}
@inproceedings {MahmoodWittepscheund2011,
	title = {Multi-source image classification using color attribute profiles},
	booktitle = {3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
	year = {2011},
	pages = {1 - 4},
	address = {Lisbon, Portugal},
	abstract = {This work introduces a method to extract attribute profiles from RGB color images with high spatial resolution, for instance images acquired from Unmanned Aerial Vehicles (UAV). The resulting Color Attribute Profiles (CAP) are intended to improve the classification of low spatial resolution hyperspectral images by merging the attribute features with the spectral features of the hyperspectral image. Instead of treating the R, G and B bands separately, the color image is transformed into CIE-Lab space. In this color space, attribute profiles are extracted from the {\textquoteleft}L{\textquoteright} band, while the {\textquoteleft}a{\textquoteright} and {\textquoteleft}b{\textquoteright} bands are kept intact, and the resulting images are transformed back into RGB space. In our experiments, classification results using this methodology are compared to classification results using other strategies for extracting attribute profiles in CIE-Lab space, as well as regular grayscale attribute profiles.},
	keywords = {Attributes, Classification, Color, Hyperspectral, Morphology},
	isbn = {978-1-4577-2202-8},
	issn = {2158-6268},
	doi = {10.1109/WHISPERS.2011.6080859},
	url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=6080859\&isnumber=6080842},
	author = {Zahid Mahmood and Guy Thoonen and Val{\'e}rie De Witte and Paul Scheunders}
}
@article {P.M.A.S.bjeurissJ.A.M.K.F.T.J.-F.C.2011,
	title = {Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom},
	journal = {NeuroImage},
	volume = {56},
	number = {1},
	year = {2011},
	month = {May},
	pages = {220-234},
	author = {Pierre Fillard and Maxime Descoteaux and Alvina Goh and Sylvain Gouttard and Ben Jeurissen and James Malcolm and Alonso Ramirez-Manzanares and Marco Reisert and Ken Sakaie and Fatima Tensaouti and Ting-Shou Yo and Jean-Fran{\c c}ois Mangin and Cyril Poupon}
}
@article {1269,
	title = {Successive Cambia: A Developmental Oddity or an Adaptive Structure?},
	journal = {PLoS ONE},
	volume = {6},
	year = {2011},
	month = {1/2011},
	pages = {e16558},
	doi = {10.1371/journal.pone.0016558},
	author = {Robert, Elisabeth M. R. and Schmitz, Nele and Boeren, Ilse and Driessens, Tess and Herremans, Kristof and Johan De Mey and Elke Van de Casteele and Beeckman, Hans and Koedam, Nico},
	editor = {Peer, Wendy}
}
@conference {1553,
	title = {White Matter Tract Deficits in Schizophrenia},
	volume = {7},
	year = {2011},
	address = {Dublin, Ireland},
	author = {Forde, Natalie J and Ellison-Wright, I and Nathan, Pradeep J and Zaman, R and Dudas, R and Agius, M and Fernandez-Egea, E and Alexander Leemans and Ben Jeurissen and Scanlon, Cathy and Colm McDonald and Dara M. Cannon}
}
@article {wvheckeAleemanssdbackerBjeurisspmparizejsijbers2010,
	title = {Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study},
	journal = {Human Brain Mapping},
	volume = {31},
	number = {1},
	year = {2010},
	pages = {98-114},
	author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Ben Jeurissen and Paul M Parizel and Jan Sijbers}
}
@inproceedings {1322,
	title = {Iterative correction of beam hardening artifacts in CT},
	booktitle = {The First International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2010},
	month = {06/2010},
	author = {Van Slambrouck, Katrien and Gert Van Gompel and M. Defrise and Kees Joost Batenburg and Jan Sijbers and Johan Nuyts}
}
@article {jjuntujsijberssdbackerjrajandvandyck2010,
	title = {A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images},
	journal = {Journal of Magnetic Resonance Imaging},
	volume = {31},
	year = {2010},
	pages = {680{\textendash}689},
	doi = {10.1002/jmri.22095},
	author = {Juntu, Jaber and Jan Sijbers and Steve De Backer and Jeny Rajan and Dirk Van Dyck}
}
@article {1479,
	title = {Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson{\textquoteright}s disease discerned with microSPECT and quantitative MRI.},
	journal = {Magnetic Resonance Materials in Physics, Biology and Medicine},
	volume = {23},
	year = {2010},
	month = {04/2010},
	pages = {65-75},
	abstract = {OBJECT: In the present study, we aimed to evaluate the impact of neurodegeneration of the nigrostriatal tract in a rodent model of Parkinson{\textquoteright}s disease on the different MR contrasts (T(2), T(1), CBF and CBV) measured in the striatum.

MATERIAL AND METHODS: Animals were injected with 6-hydroxydopamine (6OHDA) in the substantia nigra resulting in massive loss of nigrostriatal neurons and hence dopamine depletion in the ipsilateral striatum. Using 7T MRI imaging, we have quantified T(2), T(1), CBF and CBV in the striata of 6OHDA and control rats. To validate the lesion size, behavioral testing, dopamine transporter muSPECT and tyrosine hydroxylase staining were performed.

RESULTS: No significant differences were demonstrated in the absolute MRI values between 6OHDA animals and controls; however, 6OHDA animals showed significant striatal asymmetry for all MRI parameters in contrast to controls.

CONCLUSIONS: These PD-related asymmetry ratios might be the result of counteracting changes in both intact and affected striatum and allowed us to diagnose PD lesions. As lateralization is known to occur also in PD patients and might be expected in transgenic PD models as well, we propose that MR-derived asymmetry ratios in the striatum might be a useful tool for in vivo phenotyping of animal models of PD.},
	keywords = {Animals, Corpus Striatum, Disease Models, Animal, Female, Magnetic Resonance Imaging, Oxidopamine, Parkinsonian Disorders, Positron-Emission Tomography, Rats, Rats, Wistar, Reproducibility of Results, Sensitivity and Specificity},
	issn = {1352-8661},
	doi = {10.1007/s10334-010-0198-7},
	author = {N. Van Camp and Vreys, Ruth and Koen Van Laere and E. Lauwers and Dirk Beque and Marleen Verhoye and Casteels, Cindy and Alfons Verbruggen and Zeger Debyser and Luc Mortelmans and Jan Sijbers and Johan Nuyts and Veerle Baekelandt and Annemie Van Der Linden}
}
@inproceedings {Haest10,
	title = {An object-based approach to quantity and quality assessment of heathland habitats in the framework of NATURA 2000 using hyperspectral airborne AHS images.},
	booktitle = {Proceedings of GEOBIA 2010, the Geographic Object-Based Image Analysis Conference},
	volume = {XXXVIII-4/C7},
	year = {2010},
	month = {July},
	abstract = {Straightforward mapping of detailed heathland habitat patches and their quality using remote sensing is hampered by (1) the intrinsic property of a high heterogeneity in habitat species composition (i.e. high intra-variability), and (2) the occurrence of the same species in multiple habitat types (i.e. low inter-variability). Mapping accuracy of detailed habitat objects can however be improved by using an advanced approach that specifically takes into account and exploits these inherent patch characteristics. To demonstrate the idea, we developed and applied a multi-step mapping framework on a protected semi-natural heathland area in the north of Belgium. The method consecutively consists of (1) a 4-level hierarchical land cover classification of hyperspectral airborne AHS image data, and (2) a kernel-based structural re-classification algorithm in combination with habitat patch object composition definitions. Detailed land cover composition data were collected in 1325 field plots. Multi-variate analysis (Wards clustering; TWINSPAN) of these data led to the design of meaningful land cover classes in a dedicated classification scheme. Subsequently, the data were used as reference for the classification of hyperspectral AHS image data. Linear Discriminant Analysis in combination with Sequential-Floating-Forward-Selection (SFFS-LDA) was applied to classify the hyperspectral images. Classification accuracies of these maps are in the order of 74-93\% (Kappa= 0.81-0.92) depending on the classification detail. To subsequently obtain habitat patch (object) maps, the land cover classifications were used as input for a kernel-based spatial re-classification process, in combination with a rule-set that relates specific Natura 2000 habitats with a composition range of the land cover classes. The resulting habitat patch maps illustrate the methodologys potential for detailed heathland habitat characterization using hyperspectral image data, and hence contribute to the improved mapping and understanding of heathland habitat, essential for the EU member states reporting obligations under the Habitats Directive.},
	keywords = {Application, Classification, Contextual, Ecosystem, Hyper spectral, Landscape, Object, Vegetation},
	url = {http://www.isprs.org/proceedings/XXXVIII/4-C7/papers\%20proceedings/Haest_211_An_object-based_approach_to_quantity_and_quality_assessment_of_heath_land_habitats.pdf},
	author = {Haest, B. and Guy Thoonen and Jeroen Vanden Borre and Toon Spanhove and Stephanie Delalieux and L. Bertels and Kooistra, L. and C A M{\"u}cher and Paul Scheunders}
}
@article {dpootajdendekAchtenmverhoyejsijbers2010,
	title = {Optimal experimental design for Diffusion Kurtosis Imaging},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {29},
	number = {3},
	year = {2010},
	pages = {819-829},
	doi = {http://dx.doi.org/10.1109/TMI.2009.2037915},
	author = {Dirk H J Poot and Arnold Jan den Dekker and Eric Achten and Marleen Verhoye and Jan Sijbers}
}
@mastersthesis {1290,
	title = {Advances in the reconstruction and statistical processing of Magnetic Resonance images},
	volume = {PhD in Sciences: Physics},
	year = {2009},
	type = {PhD Thesis},
	author = {Dirk H J Poot}
}
@inproceedings {Thoonen09,
	title = {Assessing the quality of heathland vegetation by classification of hyperspectral data using spatial information},
	booktitle = {Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009},
	volume = {4},
	year = {2009},
	month = {July},
	pages = {IV-330 - IV-333},
	address = {Cape Town, South Africa},
	abstract = {This article deals with a method for acquiring vegetation maps, suitable for monitoring and evaluating the conservation status of heathland vegetation from hyperspectral data. The applied method is a recursive supervised segmentation algorithm based on a Tree-structured Markov Random Field (TS-MRF), capable of incorporating structural dependencies in the classification process. To this end, a tree structure is used that is built upon structural dependencies that are present in the field. The classification results from this TS-MRF with extended tree are compared to pixel-based classification results, results from a simple smoothing post-processing, and the result from the original binary TS-MRF technique.},
	keywords = {geophysical signal processing, heathland vegetation conservation, heathland vegetation quality, hyperspectral data classification, image segmentation, Markov processes, pixel based classification comparison, recursive supervised segmentation algorithm, smoothing post processing comparison, spatial information, tree structured Markov random field, trees (mathematics), TS-MRF, vegetation mapping, vegetation maps},
	isbn = {978-1-4244-3394-0},
	doi = {10.1109/IGARSS.2009.5417380},
	author = {Guy Thoonen and Jeroen Vanden Borre and Steve De Backer and Paul Scheunders}
}
@inproceedings {aduijstepscheund2009,
	title = {A combined hyperspectral image restoration and fusion approach},
	booktitle = {IEEE International Geoscience and Remote Sensing Symposium, Cape Town, South Africa, July, 13-17},
	number = {3},
	year = {2009},
	pages = {995-998},
	author = {Y. Zhang and A. Duijster and Paul Scheunders}
}
@article {wvheckejsijberssdbackerdpootParizelaleemans2009,
	title = {On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods},
	journal = {NeuroImage},
	volume = {46},
	number = {3},
	year = {2009},
	month = {July},
	pages = {692-707},
	doi = {10.1016/j.neuroimage.2008.07.006},
	author = {Wim Van Hecke and Jan Sijbers and Steve De Backer and Dirk H J Poot and Paul M Parizel and Alexander Leemans}
}
@conference {BlockxmverhoyeGroofAudekerkeRaberdpootjsijbersHorstenavdlinde2009,
	title = {Diffusion Kurtosis Imaging (DKI) reveals an early phenotype (P30) in a transgenic rat model for Huntington{\textquoteright}s disease},
	volume = {2009},
	year = {2009},
	month = {April},
	pages = {359},
	author = {Ines Blockx and Marleen Verhoye and G. De Groof and Johan Van Audekerke and Kerstin Raber and Dirk H J Poot and Jan Sijbers and S. von Horsten and Annemie Van Der Linden}
}
@conference {PalaciosmverhoyeAudekerkedpootjsijbersWiborgavdlinde2009,
	title = {DKI visualizes hippocampal alterations in the chronic mild stress ratmodel},
	volume = {2009},
	year = {2009},
	month = {April},
	pages = {744},
	author = {Rafael  Delgado Y Palacios and Marleen Verhoye and Johan Van Audekerke and Dirk H J Poot and Jan Sijbers and O. Wiborg and Annemie Van Der Linden}
}
@article {PostnovSchutterjsijbersKarperienClerck2009,
	title = {Glucocorticoid-Induced Osteoporosis in Growing Mice Is Not Prevented by Simultaneous Intermittent PTH Treatment},
	journal = {Calcified Tissue International},
	volume = {85},
	number = {6},
	year = {2009},
	month = {December},
	pages = {530-537},
	doi = {10.1007/s00223-009-9301-3},
	author = {A. Postnov and T. De Schutter and Jan Sijbers and M. Karperien and N. De Clerck}
}
@inproceedings {Zhangaduijstepscheund2009,
	title = {A Hyperspectral Image Restoration technique},
	booktitle = {IEEE International Conference on Image Processing, Cairo, Egypt, November 7-11},
	year = {2009},
	pages = {2873-2876},
	author = {Y. Zhang and A. Duijster and Paul Scheunders}
}
@article {ajdendekdpootBosjsijbers2009,
	title = {Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {28},
	number = {2},
	year = {2009},
	month = {February},
	pages = {287-296},
	author = {Arnold Jan den Dekker and Dirk H J Poot and R. Bos and Jan Sijbers}
}
@article {Zhangsdbackerpscheund2009,
	title = {Noise-resistant wavelet-based Bayesian fusion of multispectral and hyperspectral images},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {47},
	number = {11},
	year = {2009},
	pages = {3834-3843},
	author = {Y. Zhang and Steve De Backer and Paul Scheunders}
}
@conference {dpootajdendekmverhoyeBlockxAudekerkeavdlindejsijbers2009,
	title = {Optimizing the Diffusion Weighting Gradients for Diffusion-Kurtosis Imaging},
	volume = {2009},
	year = {2009},
	month = {April},
	pages = {1394},
	author = {Dirk H J Poot and Arnold Jan den Dekker and Marleen Verhoye and Ines Blockx and Johan Van Audekerke and Annemie Van Der Linden and Jan Sijbers}
}
@conference {dpootajdendekjsijbers2009,
	title = {Pearson Set of Distributions as Improved Signal Model for Diffusion Kurtosis Imaging},
	year = {2009},
	month = {April},
	pages = {1383},
	publisher = {ISMRM},
	author = {Dirk H J Poot and Arnold Jan den Dekker and Jan Sijbers}
}
@article {gvgompelDefrisejbatenbu2009,
	title = {Reconstruction of a uniform star object from interior x-ray data: uniqueness, stability and algorithm},
	journal = {Inverse Problems},
	volume = {25},
	number = {65010},
	year = {2009},
	month = {June},
	doi = {10.1088/0266-5611/25/6/065010},
	author = {Gert Van Gompel and M. Defrise and Kees Joost Batenburg}
}
@inproceedings {Driesen09,
	title = {Spatial hyperspectral image classification by prior segmentation},
	booktitle = {Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009},
	volume = {3},
	year = {2009},
	month = {July},
	pages = {III-709 - III-712},
	address = {Cape Town, South Africa},
	abstract = {In this paper, we propose a technique to incorporate spatial features in the classification of hyperspectral data by means of a prior segmentation of the dataset. The key idea of the technique is that each pixel is not classified individually, but that the regions obtained from the prior segmentation are classified as a whole. The proposed technique is validated on a hyperspectral dataset of a heathland area in Belgium. Experimental results show that we can achieve larger and spatially smoothed regions, while the overall classification success rate is comparable to the pure spectral classification results.},
	keywords = {Belgium, geophysical image processing, heathland area, hyperspectral data classification, image classification, image segmentation, prior segmentation, remote sensing, spatial hyperspectral image classification, spatially smoothed regions, spectral classification},
	isbn = {978-1-4244-3394-0},
	doi = {10.1109/IGARSS.2009.5417861},
	author = {J. Driesen and Guy Thoonen and Paul Scheunders}
}
@inproceedings {1297,
	title = {Three-dimensional monitoring of physical weathering in limestone with X-ray computed microtomography (micro-CT)},
	booktitle = {12th Euroseminar on Microscopy Applied to Building Materials (EMABM)},
	year = {2009},
	author = {Boone, M.A. and De Kock, T. and Dewanckele, J. and Cnudde, Veerle and Boone, M.N. and Van Loo, D. and Elke Van de Casteele and De Schutter, G. and Jacobs, P.}
}
@article {wvdbroekVerbeeckSchryverssdbackerpscheund2009,
	title = {Tomographic Spectroscopic Imaging; an experimental proof of concept},
	journal = {Ultramicroscopy},
	volume = {109},
	year = {2009},
	pages = {296-303},
	author = {Wouter Van den Broek and Jo Verbeeck and D. Schryvers and Steve De Backer and Paul Scheunders}
}
@mastersthesis {1270,
	title = {Towards accurate image reconstruction from truncated X-ray CT projections},
	year = {2009},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	author = {Gert Van Gompel}
}
@inproceedings {Gansemanpscheundwdhaes2009,
	title = {Using XML-formatted scores in real-time applications},
	booktitle = {10-th International Society for Music Information Retrieval Conference, pp. 663-668, Kobe, Japan, October 26-30},
	year = {2009},
	pages = {663-668},
	author = {Joachim Ganseman and Paul Scheunders and W. D{\textquoteright}haes}
}
@article {aduijstepscheundsdbacker2009,
	title = {Wavelet-Based EM Algorithm for Multispectral-Image Restoration},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {47},
	number = {11},
	year = {2009},
	month = {November},
	pages = {3892-3898},
	author = {A. Duijster and Paul Scheunders and Steve De Backer}
}
@inproceedings {Zhangsdbackerpscheund2008,
	title = {Bayesian fusion of multispectral and hyperspectral image in wavelet domain},
	booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008, Boston, United States, 6-11 July},
	year = {2008},
	pages = {69-72},
	publisher = {IEEE International},
	organization = {IEEE International},
	author = {Y. Zhang and Steve De Backer and Paul Scheunders},
	editor = {t.b.a.}
}
@inproceedings {wvheckealeemanssdbackerParizeljsijbers2008,
	title = {On the construction of a ground truth methodology to evaluate VBM analysis results of diffusion tensor images},
	booktitle = {European Society for Magnetic Resonance in Medicine and Biology},
	year = {2008},
	month = {October},
	address = {Valencia, Spain},
	author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Paul M Parizel and Jan Sijbers}
}
@article {wvheckejsijbersDagostinoMaessdbackerVandervlietParizelaleemans2008,
	title = {On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain},
	journal = {NeuroImage},
	volume = {43},
	number = {1},
	year = {2008},
	pages = {69-80},
	doi = {0.1016/j.neuroimage.2008.07.006},
	author = {Wim Van Hecke and Jan Sijbers and E. Dagostino and F. Maes and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Alexander Leemans}
}
@article {sdbackerPizuricaHuysmansPhilipspscheund2008,
	title = {Denoising of Multicomponent Images Using Wavelet Least-Squares Estimators},
	journal = {Image and Vision Computing},
	volume = {26},
	number = {7},
	year = {2008},
	month = {July},
	pages = {1038-1051},
	author = {Steve De Backer and Aleksandra Pizurica and B. Huysmans and Wilfried Philips and Paul Scheunders}
}
@inproceedings {wvheckealeemansAgostinosdbackerVandervlietParizeljsijbers2008,
	title = {The evaluation of a population based diffusion tensor image atlas using a ground truth method},
	booktitle = {Proceedings of SPIE Medical Imaging},
	volume = {6914},
	year = {2008},
	month = {February},
	address = {San Diego, USA},
	author = {Wim Van Hecke and Alexander Leemans and E. Dagostino and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers}
}
@inproceedings {dpootjsijbersajdendek2008,
	title = {An exploration of spatial similarities in temporal noise spectra in fMRI measurements},
	booktitle = {Proceedings of SPIE Medical Imaging 2008},
	volume = {6914},
	year = {2008},
	month = {February},
	pages = {69142},
	address = {San Diego, CA, USA},
	author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@conference {wvheckealeemanssdbackerVandervlietjsijberspmparize2008,
	title = {A Ground Truth Analysis of the Preservation of Diffusion Tensor Information in a Population Specific Atlas},
	year = {2008},
	month = {May},
	address = {Toronto, Canada},
	author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Jan Sijbers and Paul M Parizel}
}
@conference {gvgompeljbatenbuDefrisejsijbers2008,
	title = {An iterative post-reconstruction method for beam hardening reduction without prior information},
	year = {2008},
	month = {March},
	author = {Gert Van Gompel and Kees Joost Batenburg and M. Defrise and Jan Sijbers}
}
@article {KempeneersZarco-TejadaNorthsdbackerDelalieuxSepulcre-CantoMoralesAardtSagardoyCoppinpscheund2008,
	title = {Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery},
	journal = {International Journal of Remote Sensing},
	volume = {29},
	number = {17},
	year = {2008},
	pages = {5093-5111},
	author = {Pieter Kempeneers and P.J. Zarco-Tejada and P.R.J. North and Steve De Backer and Stephanie Delalieux and G. Sepulcre-Canto and F. Morales and Jan van Aardt and Ruth Sagardoy and P. Coppin and Paul Scheunders}
}
@article {sdbackerCornelissenLemeireNuydensMeertSchelkenspscheund2008,
	title = {Mosiacing of Fibered Fluorescence Microscopy Video},
	journal = {Lecture notes in Computer Science},
	volume = {5259},
	year = {2008},
	month = {October},
	pages = {915-923},
	author = {Steve De Backer and F. Cornelissen and J. Lemeire and R. Nuydens and T. Meert and P. Schelkens and Paul Scheunders}
}
@article {jdriesenpscheund2008,
	title = {A Multicomponent Image Segmentation Framework},
	journal = {Lecture Notes in Computer Science},
	volume = {5259},
	year = {2008},
	pages = {589-600},
	author = {J. Driesen and Paul Scheunders}
}
@inproceedings {Verdoolaegesdbackerpscheund2008,
	title = {Multiscale colour texture retrieval using the geodesic distance between multivariate generalized Gaussian models},
	booktitle = {IEEE, International Conference on Image Processing, San Diego, CA, October 12-15},
	year = {2008},
	pages = {169-172},
	author = {G. Verdoolaege and Steve De Backer and Paul Scheunders}
}
@inproceedings {dpootjsijbersajdendek2008,
	title = {Optimizing the Diffusion Kurtosis imaging acquisition},
	booktitle = {European Society for Magnetic Resonance in Medicine and Biology},
	year = {2008},
	month = {October},
	address = {Valencia, Spain},
	author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {gvgompelDefrisejbatenbu2008,
	title = {Reconstruction of a uniform star object from interior X-ray data},
	booktitle = {Nuclear Science Symposium Conference Record, NSS08, IEEE},
	number = {2},
	year = {2008},
	month = {October},
	pages = {4115-4119},
	address = {Dresden, Germany},
	author = {Gert Van Gompel and M. Defrise and Kees Joost Batenburg}
}
@inproceedings {Thoonen08,
	title = {Spatial Classification of Hyperspectral Data of Dune Vegetation along the Belgian Coast},
	booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International},
	volume = {3},
	year = {2008},
	month = {July},
	pages = {III-483 - III-486},
	address = {Boston, MA, USA},
	abstract = {This work evaluates a classification method, including spatial information, for dune vegetation along the Belgian coastline. The used method is a recursive supervised segmentation algorithm based on a tree-structured Markov Random Field. This technique describes a K-ary field as a sequence of binary Markov Random Fields, each of which is represented by a node in the tree. The obtained classification results were compared to results with the same data set, for a purely spectral classification and a spectral classification, followed by spatial smoothing.},
	keywords = {airborne data, airborne radar, Belgian Coast, binary Markov Random Field, dune environment, dune vegetation mapping, Europe, hyperspectral data, image classification, image segmentation, Markov processes, spatial classification, spatial smoothing, supervised segmentation algorithm, tree-structured Markov Random Field, trees (mathematics), TS-MRF model, vegetation mapping},
	isbn = {978-1-4244-2807-6},
	doi = {10.1109/IGARSS.2008.4779389},
	author = {Guy Thoonen and Steve De Backer and S. Provoost and Pieter Kempeneers and Paul Scheunders}
}
@inproceedings {pscheundwdhaes2008,
	title = {Using MusicXML in real-time applications},
	booktitle = {Proceedings of the 34th Euromicro conference on Software Engineering and Advanced Applications, Parma, Italy, September 3-5},
	year = {2008},
	pages = {29-30},
	author = {Joachim Ganseman and Paul Scheunders and W. D{\textquoteright}haes}
}
@inproceedings {Gansemanpscheundwdhaes2008,
	title = {Using XQUERY on MusicXML databases for musicological analysis},
	booktitle = {ISMIR 2008, 9-th International Conference on Music Information Retrieval, Philadephia, USA, 14-18 september},
	year = {2008},
	pages = {433-438},
	author = {Joachim Ganseman and Paul Scheunders and W. D{\textquoteright}haes}
}
@inproceedings {aduijstesdbackerpscheund2008,
	title = {Wavelet-based Multispectral Image Restoration},
	booktitle = {IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium},
	volume = {3},
	year = {2008},
	pages = {79-82},
	publisher = {IEEE International},
	organization = {IEEE International},
	author = {A. Duijster and Steve De Backer and Paul Scheunders}
}
@article {jsijbersdpootajdendekwpintjen2007,
	title = {Automatic estimation of the noise variance from the histogram of a magnetic resonance image},
	journal = {Physics in Medicine and Biology},
	volume = {52},
	number = {5},
	year = {2007},
	month = {February},
	pages = {1335-1348},
	doi = {10.1088/0031-9155/52/5/009},
	author = {Jan Sijbers and Dirk H J Poot and Arnold Jan den Dekker and W. Pintjens}
}
@inproceedings {pscheundsdbackerPizuricaHuysmansPhilips2007,
	title = {Bayesian Wavelet-based Denoising of Multicomponent Images},
	booktitle = {Proceedings Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, 9-12 september, Vol. 6763-OK (12 pages)},
	year = {2007},
	author = {Paul Scheunders and Steve De Backer and Aleksandra Pizurica and B. Huysmans and Wilfried Philips}
}
@inproceedings {wvheckeDagostinoaleemansParizelMaesjsijbers2007,
	title = {On the construction of a healthy brain inter-subject diffusion tensor image and tractography atlas},
	booktitle = {32nd Congress of the Europea Society of NeuroRadiolog},
	year = {2007},
	pages = {146},
	author = {Wim Van Hecke and E. Dagostino and Alexander Leemans and Paul M Parizel and F. Maes and Jan Sijbers}
}
@inproceedings {wvheckealeemansBrabanderLaridonClaeysCeulemansGoethemParizeljsijbers2007,
	title = {Diffusion Tensor Fiber Tracking Reveals Probst Bundles in Patients with Agenesis of the Corpus Callosum},
	booktitle = {32nd Congress of the Europea Society of NeuroRadiolog},
	year = {2007},
	pages = {135},
	author = {Wim Van Hecke and Alexander Leemans and N. De Brabander and A. Laridon and K. Claeys and B. Ceulemans and J. Van Goethem and Paul M Parizel and Jan Sijbers}
}
@inproceedings {PeersmanVanhoenackerBrysDyckStamVerstraeteBloemHeymanHerendaeljsijbersSchepper2007,
	title = {Imaging features of Ewing{\textquoteright}s sarcoma},
	booktitle = {International Skeletal Society 2007, 34th annual ISS Radiology Refresher Course},
	year = {2007},
	month = {October},
	pages = {22},
	address = {Budapest},
	author = {B. Peersman and F. M. Vanhoenacker and P. Brys and Pieter Van Dyck and M. Stam and K. L. Verstraete and J. L. Bloem and S. Heyman and B. Van Herendael and Jan Sijbers and A. M. De Schepper}
}
@article {aduijstesdbackerpscheund2007,
	title = {Multicomponent image restoration, an experimental study},
	journal = {Lecture Notes in Computer Science},
	volume = {4633},
	year = {2007},
	pages = {58-68},
	author = {A. Duijster and Steve De Backer and Paul Scheunders}
}
@article {wvheckealeemansD{\textquoteright}AgostinosdbackerVandervlietParizeljsijbers2007,
	title = {Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {26},
	number = {11},
	year = {2007},
	pages = {1598-1612},
	author = {Wim Van Hecke and Alexander Leemans and E. Dagostino and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers}
}
@article {pscheundsdbacker2007,
	title = {Wavelet denoising of multicomponent images, using Gaussian Scale Mixture models and a noise-free image as priors},
	journal = {IEEE Transactions on Image Processing},
	volume = {16},
	number = {7},
	year = {2007},
	month = {July},
	pages = {1865-1872},
	author = {Paul Scheunders and Steve De Backer}
}
@inproceedings {aduijstesdbackerpscheund2007,
	title = {Wavelet-based Multicomponent Image Restoration},
	booktitle = {Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, United States, September 9-12},
	series = {Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference},
	volume = {6763},
	year = {2007},
	month = {October},
	author = {A. Duijster and Steve De Backer and Paul Scheunders},
	editor = {F. Truchetet and O. Laligant}
}
@article {wvdbroekVerbeecksdbackerpscheundSchryvers2006,
	title = {Acquisition of the EELS data cube by tomographic reconstruction},
	journal = {Ultramicroscopy},
	volume = {106},
	number = {3},
	year = {2006},
	month = {March},
	pages = {269-276},
	author = {Wouter Van den Broek and Jo Verbeeck and Steve De Backer and Paul Scheunders and D. Schryvers}
}
@inproceedings {dpootjsijbersDekkerwpintjen2006,
	title = {Automatic estimation of the noise variance from the histogram of a magnetic resonance image},
	booktitle = {IEEE/EBMS Benelux Symposium proceedings},
	year = {2006},
	month = {December},
	pages = {135-138},
	publisher = {IEEE/EMBS},
	organization = {IEEE/EMBS},
	author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker and W. Pintjens}
}
@inproceedings {KempeneerssdbackerZarco-TejadaDelalieuxSepulcre-Cant{\'o}MoralesSagardoyAardtCoppinpscheund2006,
	title = {Chlorophyll retrieval from canopy reflectance over orchards using hyperspectral techniques},
	booktitle = {2nd International Symposium on Recent Advances in Quantitative Remote Sensing, 25-29 September 2006, Torrent (Valencia), Spain},
	year = {2006},
	author = {Pieter Kempeneers and Steve De Backer and P.J. Zarco-Tejada and Stephanie Delalieux and G. Sepulcre-Cant{\'o} and F. Morales and Ruth Sagardoy and Jan van Aardt and P. Coppin and Paul Scheunders}
}
@inproceedings {gvgompelDefrisedvandyck2006,
	title = {Consistent Extrapolation of Truncated 2D CT Projections},
	booktitle = {Micro tomography 3D},
	year = {2006},
	month = {September},
	address = {Gasthuisberg, Leuven, Belgium},
	author = {Gert Van Gompel and M. Defrise and Dirk Van Dyck}
}
@inproceedings {wvheckealeemansBrabanderLaridonCeulemansJParizel2006,
	title = {Diffusion tensor fiber tracking in patients with agenesis of the corpus callosum},
	booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology},
	year = {2006},
	pages = {34-35},
	address = {Warsaw, Poland},
	author = {Wim Van Hecke and Alexander Leemans and N. De Brabander and A. Laridon and B. Ceulemans and Jan Sijbers and Paul M Parizel}
}
@inproceedings {gvgompelDefrisedvandyck2006,
	title = {Elliptical Extrapolation of Truncated 2D CT Projections using Helgason-Ludwig consistency conditions},
	booktitle = {SPIE Medical Imaging: Physics of Medical Imaging},
	series = {Proceedings of the SPIE},
	volume = {6142},
	year = {2006},
	month = {February},
	pages = {1408-1417},
	address = {San Diego, Californa, USA},
	author = {Gert Van Gompel and M. Defrise and Dirk Van Dyck},
	editor = {Flynn, Michael J.; Hsieh, Jiang.}
}
@inproceedings {sdbackerpscheund2006,
	title = {Enhancement of fMRI image series with the aid of an anatomical image},
	booktitle = {ISBI{\textquoteright}06, IEEE International Symposium on Biomedical Imaging, Arlington, Virginia, april 6-9},
	year = {2006},
	pages = {1052-1055},
	author = {Steve De Backer and Paul Scheunders}
}
@inproceedings {dpootjsijbersajdendekBos2006,
	title = {Estimation of the noise variance from the background histogram mode of an MR image},
	booktitle = {Proceedings of the 25th Benelux Meeting on Systems and Control},
	series = {TuM06-5},
	year = {2006},
	month = {March},
	address = {Heeze, The Netherlands},
	author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker and R. Bos}
}
@inproceedings {dpootjsijbersajdendekBos2006,
	title = {Estimation of the noise variance from the background histogram mode of an MR image},
	booktitle = {Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium)},
	year = {2006},
	month = {March},
	pages = {159-162},
	address = {Antwerp, Belgium},
	author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker and R. Bos}
}
@inproceedings {NagelsVandervlietwvheckeEngelborghshoogheCrasParizelDeyn2006,
	title = {fMRI during PASAT and PVSAT in mild MS, moderate MS and normal volunteers.},
	booktitle = {22nd Congress of the European Committee for},
	year = {2006},
	address = {Madrid, Spain},
	author = {Guy Nagels and Everhard Vandervliet and Wim Van Hecke and Sebastiaan Engelborghs and M.B. D hooghe and P. Cras and Paul M Parizel and P.P. De Deyn}
}
@article {GroofmverhoyeMeirTindemansaleemansavdlinde2006,
	title = {In vivo diffusion tensor imaging (DTI) of brain subdivisions and vocal pathways in songbirds},
	journal = {NeuroImage},
	volume = {29},
	year = {2006},
	pages = {754-763},
	author = {G. De Groof and Marleen Verhoye and V. Van Meir and I. Tindemans and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {wvheckealeemanssdbackerVandervlietParizelAgostinojsijbers2006,
	title = {Multi-channel coregistration of diffusion tensor images based on a viscous fluid model},
	booktitle = {Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium},
	year = {2006},
	pages = {139-142},
	address = {Brussels, Belgium},
	author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Paul M Parizel and E. Dagostino and Jan Sijbers}
}
@article {aleemansjsijberssdbackerVandervlietParizel2006,
	title = {Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data},
	journal = {Magnetic Resonance in Medicine},
	volume = {55},
	number = {6},
	year = {2006},
	pages = {1414-1423},
	author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel}
}
@inproceedings {aleemansjsijberssdbackerVandervlietParizel2006,
	title = {Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data},
	booktitle = {14th Scientific Meeting - International Society for Magnetic Resonance in Medicine},
	year = {2006},
	pages = {437},
	address = {Seattle, USA},
	author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel}
}
@inproceedings {wvheckealeemanssdbackerVandervlietParizeljsijbersAgostino2006,
	title = {Non-rigid coregistration of diffusion tensor images using a viscous fluid model.},
	booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology},
	year = {2006},
	pages = {191-192},
	address = {Warsaw, Poland},
	author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers and E. Dagostino}
}
@inproceedings {Groofmverhoyealeemansjsijbersavdlinde2006,
	title = {Paired voxel-wise statistical mapping of in vivo Diffusion Tensor Imaging (DTI) data to assess the seasonal neuronal plasticity in the brain of a songbird},
	booktitle = {1st Annual Meeting - European Society of Molecular Imaging},
	year = {2006},
	address = {Paris, France},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Jan Sijbers and Annemie Van Der Linden}
}
@inproceedings {slamenswdhaes2006,
	title = {Parameter Optimizations Methods for the EDS Model},
	booktitle = {2006 IEEE International Conference on Acoustics, Speech and Signal Processing},
	year = {2006},
	month = {May},
	address = {Toulouse, France},
	author = {S. Lamens and W. D{\textquoteright}haes}
}
@inproceedings {jsijbersajdendekdpootBosmverhoyeCampavdlinde2006,
	title = {Robust estimation of the noise variance from background MR data},
	booktitle = {Proceedings of SPIE Medical Imaging: Image Processing},
	volume = {6144},
	year = {2006},
	month = {February},
	pages = {2018-2028},
	address = {San Diego, CA, USA},
	author = {Jan Sijbers and Arnold Jan den Dekker and Dirk H J Poot and R. Bos and Marleen Verhoye and N. Van Camp and Annemie Van Der Linden}
}
@inproceedings {KempeneerssdbackerTejadaDelalieuxCantoIribasAardtCoppinpscheund2006,
	title = {Stress detection in orchards with hyperspectral remote sensing data},
	booktitle = {SPIE Remote Sensing, Stockholm, Sweden, september 11-14},
	volume = {6359},
	number = {38},
	year = {2006},
	month = {September},
	author = {Pieter Kempeneers and Steve De Backer and P J Zarco Tejada and Stephanie Delalieux and G Sepulcre Canto and F Morales Iribas and Jan van Aardt and P. Coppin and Paul Scheunders}
}
@inproceedings {Groofmverhoyealeemansavdlinde2006,
	title = {Using diffusion tensor imaging (DTI) to assess the neuronal plasticity and neuroconnectivity in the brain of a songbird},
	booktitle = {Molecular \& Cellular Basis of Neuroconnectivity},
	year = {2006},
	address = {Leuven, Belgium},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {Groofmverhoyealeemansavdlinde2006,
	title = {Using diffusion tensor imaging (DTI) to assess the neuronal plasticity in the brain of a songbird},
	booktitle = {XXeme Congres du Groupement d{\textquoteright}Etudes de Resonance Magnetique},
	year = {2006},
	address = {Blankenberge, Belgium},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {jdriesenpscheund2006,
	title = {Wavelet based segmentation of multi-component images},
	booktitle = {IEEE BENELUX/DSP Valley Signal Processing Symposium (SPS-DARTS) March 28-29, Antwerp, Belgium},
	year = {2006},
	pages = {151-154},
	author = {J. Driesen and Paul Scheunders}
}
@inproceedings {pscheundsdbacker2006,
	title = {Wavelet Denoising of multicomponent images using a Gaussian Scale Mixture model},
	booktitle = {ICPR{\textquoteright}06, International Conference on Pattern Recognition, Hong Kong, august 20-24},
	volume = {3},
	year = {2006},
	pages = {754-757},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	author = {Paul Scheunders and Steve De Backer}
}
@inproceedings {pscheundsdbacker2006,
	title = {Wavelet Denoising of multicomponent images using a noise-free image},
	booktitle = {ICIP{\textquoteright}06, IEEE International Conference on Image Processing, Atlanta, Georgia, October 8-11},
	year = {2006},
	pages = {2619-2622},
	publisher = {IEEE Signal Processing Society},
	organization = {IEEE Signal Processing Society},
	author = {Paul Scheunders and Steve De Backer}
}
@inproceedings {CampBlockxCamonVeramverhoyealeemansMartinezjsijbersPlanasavdlinde2006,
	title = {White and grey matters changes in a rat model for Huntington{\textquoteright}s disease discerned with in vivo DTI},
	booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology},
	year = {2006},
	pages = {210-211},
	address = {Warsaw, Poland},
	author = {N. Van Camp and Ines Blockx and L. Camon and N. de Vera and Marleen Verhoye and Alexander Leemans and E. Martinez and Jan Sijbers and A. Planas and Annemie Van Der Linden}
}
@inbook {ajdendekjsijbers2005,
	title = {Advanced Image Processing in Magnetic Resonance Imaging},
	booktitle = {Series: Signal Processing and Communications},
	volume = {27},
	year = {2005},
	note = {ISBN: 0824725425},
	month = {October},
	pages = {85-143},
	publisher = {Marcel Dekker},
	organization = {Marcel Dekker},
	chapter = {4},
	author = {Arnold Jan den Dekker and Jan Sijbers},
	editor = {L. Landini}
}
@article {aleemansjsijberssdbackerVandervlietParizel2005,
	title = {Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information},
	journal = {Lecture Notes in Computer Science},
	volume = {3708},
	year = {2005},
	pages = {523-530},
	author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel}
}
@article {sdbackerKempeneersDebruynpscheund2005,
	title = {A Band Selection Technique for Spectral Classification},
	journal = {IEEE Geoscience and Remote Sensing Letters},
	volume = {2},
	number = {3},
	year = {2005},
	month = {July},
	pages = {319-323},
	author = {Steve De Backer and Pieter Kempeneers and W. Debruyn and Paul Scheunders}
}
@inproceedings {ajdendekjsijbersBosasmolder2005,
	title = {Brain activation detection from functional magnetic resonance imaging data using likelihood based hypothesis tests},
	booktitle = {Abstracts of the 24th Benelux Meeting on Systems and Control},
	year = {2005},
	month = {March},
	address = {Houffalize, Belgium},
	author = {Arnold Jan den Dekker and Jan Sijbers and R. Bos and Alain Smolders}
}
@inproceedings {DelputtealeemansFieremansDeeneDAsselerLemahieuAchtenjsijbersWalle2005,
	title = {Density Regularized Fiber Tractography of the Brain White Matter using Diffusion Tensor MRI},
	booktitle = {13th Scientific Meeting - International Society for Magnetic Resonance in Medicine},
	year = {2005},
	pages = {1309},
	address = {Miami, USA},
	author = {S. Delputte and Alexander Leemans and Els Fieremans and Y. De Deene and Y. D{\textquoteright}Asseler and I. Lemahieu and Eric Achten and Jan Sijbers and R. Van de Walle}
}
@inproceedings {Groofmverhoyealeemansavdlinde2005,
	title = {DTI parameters: Fractional Anisotropy, Radial and Axial Diffusivity reveal seasonal neuroplasticity in the adult songbird brain},
	booktitle = {4th annual meeting of the Society of Molecular Imaging},
	year = {2005},
	address = {Keulen, Germany},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {aleemanssdbackerjsijbersVandervlietParizel2005,
	title = {End point clustering for diffusion tensor white matter fiber bundle tractography},
	booktitle = {22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology},
	year = {2005},
	pages = {129-130},
	address = {Basle, Switzerland},
	author = {Alexander Leemans and Steve De Backer and Jan Sijbers and Everhard Vandervliet and Paul M Parizel}
}
@article {jsijbersajdendek2005,
	title = {Generalized likelihood Ratio tests for complex fMRI data: a simulation study},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {24},
	number = {5},
	year = {2005},
	month = {May},
	pages = {604-611},
	doi = {10.1109/TMI.2005.844075},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@article {KempeneerssdbackerDebruynpscheund2005,
	title = {Generic Wavelet-Based Hyperspectral Classification Applied to Vegetation Stress Detection},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {43},
	year = {2005},
	month = {March},
	pages = {610-614},
	author = {Pieter Kempeneers and Steve De Backer and W. Debruyn and Paul Scheunders}
}
@inproceedings {KempeneerssdbackerDebruynProvoostpscheund2005,
	title = {Hyperspectral classification applied to the Belgian coastline},
	booktitle = {SPIE Remote Sensing, Bruges, Belgium, 19-22 september},
	volume = {5982},
	number = {15},
	year = {2005},
	author = {Pieter Kempeneers and Steve De Backer and W. Debruyn and S. Provoost and Paul Scheunders}
}
@article {ajdendekjsijbers2005,
	title = {Implications of the Rician distribution for fMRI generalized likelihood ratio tests},
	journal = {Magnetic Resonance Imaging},
	volume = {23},
	number = {9},
	year = {2005},
	pages = {953-959},
	doi = {10.1016/j.mri.2005.07.008},
	author = {Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {CampLaereVreysmverhoyeLauwersBequeMaesVerbruggenDebyserMortelmansjsijbersNuytsBaekelandtavdlinde2005,
	title = {In vivo multimodal (MRI, SPECT) imaging of the 6-OHDA rat model for Parkinson{\textquoteright}s disease correlated with behavior and histology},
	booktitle = {Belgian Society of Neuroscience},
	year = {2005},
	month = {May},
	author = {N. Van Camp and Koen Van Laere and Vreys, Ruth and Marleen Verhoye and E. Lauwers and Dirk Beque and F. Maes and Alfons Verbruggen and Zeger Debyser and Luc Mortelmans and Jan Sijbers and Johan Nuyts and Veerle Baekelandt and Annemie Van Der Linden}
}
@inproceedings {CampLaereVreysmverhoyeLauwersBequeMaesVerbruggenDebyzerMortelmansjsijbersNuytsBaekelandtavdlinde2005,
	title = {In vivo multimodal (MRI,SPECT) imaging of the 6-OHDA rat model for Parkinson{\textquoteright}s disease correlated with behavior and histology},
	booktitle = {XXIInd International Symposium on Cerebral Blood Flow, Metabolism and Function and VIIth International Conference of Quantification of Brain Function with PET},
	year = {2005},
	month = {June},
	address = {Vrije Universiteit, Amsterdam, the Netherlands},
	author = {N. Van Camp and Koen Van Laere and Vreys, Ruth and Marleen Verhoye and E. Lauwers and Dirk Beque and F. Maes and Alfons Verbruggen and Zeger Debyser and Luc Mortelmans and Jan Sijbers and Johan Nuyts and Veerle Baekelandt and Annemie Van Der Linden}
}
@inproceedings {GroofmverhoyeMeirTindemansaleemansavdlinde2005,
	title = {In Vivo Visualization of the Neuroanatomy and Brain Connectivity of Starling Brain Through Diffusion Tensor Imaging},
	booktitle = {6th Bi-Annual Meeting {\textendash} Belgian Society for Neuroscience},
	year = {2005},
	address = {Brussels, Belgium},
	author = {G. De Groof and Marleen Verhoye and V. Van Meir and I. Tindemans and Alexander Leemans and Annemie Van Der Linden}
}
@article {jsijbersajdendekBos2005,
	title = {A likelihood ratio test for functional MRI data analysis to account for colored noise},
	journal = {Lecture Notes in Computer Science},
	volume = {3708},
	year = {2005},
	month = {September},
	pages = {538-546},
	author = {Jan Sijbers and Arnold Jan den Dekker and R. Bos}
}
@inproceedings {KempeneersSterckxDebruynParkRuddicksdbackerpscheund2005,
	title = {Retrieval of oceanic constituents from ocean color using simulated annealing},
	booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, 25-29 July},
	volume = {8},
	year = {2005},
	pages = {5651-5654},
	author = {Pieter Kempeneers and S Sterckx and W. Debruyn and Y. Park and K. Ruddick and Steve De Backer and Paul Scheunders}
}
@inproceedings {Groofmverhoyealeemansavdlinde2005,
	title = {Seasonal changes in neuronal connectivity in the songbird brain discerned by repeated in vivo DTI},
	booktitle = {13th Scientific Meeting - International Society for Magnetic Resonance in Medicine},
	year = {2005},
	pages = {715},
	address = {Miami, USA},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Annemie Van Der Linden}
}
@article {MeirBoumansGroofAudekerkeasmolderpscheundjsijbersmverhoyeBalthazartavdlinde2005,
	title = {Spatiotemporal properties of the BOLD response in the songbirds auditory circuit during a variety of listening tasks},
	journal = {NeuroImage},
	volume = {25},
	year = {2005},
	pages = {1242-1255},
	author = {V. Van Meir and T. Boumans and G. De Groof and Johan Van Audekerke and Alain Smolders and Paul Scheunders and Jan Sijbers and Marleen Verhoye and J. Balthazart and Annemie Van Der Linden}
}
@inproceedings {aleemanssdbackerjsijbersVandervlietParizel2005,
	title = {TRACT: Tissue Relative Anisotropy based Curvature Thresholding for deterministic MR diffusion tensor tractography},
	booktitle = {22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology},
	year = {2005},
	pages = {289},
	address = {Basle, Switzerland},
	author = {Alexander Leemans and Steve De Backer and Jan Sijbers and Everhard Vandervliet and Paul M Parizel}
}
@inproceedings {Groofmverhoyealeemansavdlinde2005,
	title = {Using diffusion tensor imaging (DTI) to assess the neuronal plasticity in the brain of a songbird},
	booktitle = {4th Annual Symposium {\textendash} Young Belgian Magnetic Resonance Scientists},
	year = {2005},
	address = {Brussels, Belgium},
	author = {G. De Groof and Marleen Verhoye and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {jdriesenpscheund2005,
	title = {Wavelet based segmentation of multivalued images},
	booktitle = {SPIE Optics East, 23-26 October, Boston, Massachusetts USA},
	volume = {6001},
	number = {2},
	year = {2005},
	pages = {13-22},
	author = {J. Driesen and Paul Scheunders}
}
@inproceedings {pscheundsdbacker2005,
	title = {Wavelet-based enhancement of remote sensing and biomedical image series using an auxiliary image},
	booktitle = {SPIE Optics East, 23-26 October, Boston, Massachusetts USA},
	volume = {6001},
	number = {5},
	year = {2005},
	pages = {41-52},
	author = {Paul Scheunders and Steve De Backer}
}
@inproceedings {ajdendekjsijbers2004,
	title = {Brain activation detection from magnitude fMRI data using a generalized likelihood ratio test},
	booktitle = {Abstracts of the 23rd Benelux Meeting on Systems and Control},
	year = {2004},
	month = {March},
	address = {Helvoirt, The Netherlands},
	author = {Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {sdbackerKempeneersDebruynpscheund2004,
	title = {Classification of Dune Vegetation from Remotely Sensed Hyperspectral Images},
	booktitle = {Image Analysis and Recognition Proc. of International Conference on Image Analysis and Recognition},
	series = {Lecture Notes in Computer Science},
	year = {2004},
	pages = {497-503},
	publisher = {Springer},
	organization = {Springer},
	address = {Porto, Portugal},
	author = {Steve De Backer and Pieter Kempeneers and W. Debruyn and Paul Scheunders},
	editor = {A. Campilho and M. Kamel}
}
@inproceedings {KempeneerssdbackerDerondeBertelsDebruynpscheund2004,
	title = {Classifying hyperspectral airborne imagery for vegetation survey along coastlines},
	booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Anchorage, USA, 20-24 september},
	volume = {2},
	year = {2004},
	pages = {1475-1478},
	publisher = {IEEE International},
	organization = {IEEE International},
	address = {Anchorage, USA},
	author = {Pieter Kempeneers and Steve De Backer and B. Deronde and L. Bertels and W. Debruyn and Paul Scheunders}
}
@inproceedings {jsijbersajdendek2004,
	title = {Construction of a likelihood ratio test for magnitude fMRI data},
	booktitle = {19th Annual Symposium of the Belgian Hospital Physicists Association},
	year = {2004},
	month = {January},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {jsijbersCampaleemansajdendekmverhoyeavdlinde2004,
	title = {Coregistration of Micro-MRI, microCT and microPET},
	booktitle = {Workshop on non Invasive 3D Microscopy},
	year = {2004},
	month = {August},
	pages = {16},
	address = {University of Antwerp, Belgium},
	author = {Jan Sijbers and N. Van Camp and Alexander Leemans and Arnold Jan den Dekker and Marleen Verhoye and Annemie Van Der Linden}
}
@inproceedings {ajdendekjsijbers2004,
	title = {Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test},
	booktitle = {Proceedings of the 12th European Signal Processing Conference},
	year = {2004},
	month = {September},
	pages = {233-236},
	publisher = {ISBN 3-200-00165-8},
	organization = {ISBN 3-200-00165-8},
	address = {Vienna, Austria},
	author = {Arnold Jan den Dekker and Jan Sijbers},
	editor = {F. Hlawatsch and B. Wistawel}
}
@inproceedings {MeirBoumansGroofAudekerkeasmolderpscheundjsijbersmverhoyeBalthazartavdlinde2004,
	title = {Functional Magnetic resonance Imaging meets animal vocal learner},
	booktitle = {Third One-Day Symposium of Young Belgian Magnetic Resonance Scientists},
	year = {2004},
	month = {November},
	address = {Brussels, Belgium},
	author = {V. Van Meir and T. Boumans and G. De Groof and Johan Van Audekerke and Alain Smolders and Paul Scheunders and Jan Sijbers and Marleen Verhoye and J. Balthazart and Annemie Van Der Linden}
}
@inproceedings {jsijbersajdendek2004,
	title = {Generalized likelihood ratio test for complex fMRI data},
	booktitle = {SPIE Medical Imaging: Physiology, Function, and Structure from Medical Images},
	volume = {5369},
	year = {2004},
	month = {February},
	pages = {652-663},
	address = {San Diego, California, USA},
	author = {Jan Sijbers and Arnold Jan den Dekker},
	editor = {Amir. A. Amini}
}
@inproceedings {wdhaes2004,
	title = {A highly optimized method for computing amplitudes over a windowed short time signal: From O(K^2N) to O(N log(N))},
	booktitle = {Proceedings of the IEEE Benelux Signal Processing Symposium},
	year = {2004},
	address = {Hilvarenbeek, the Netherlands},
	author = {W. D{\textquoteright}haes}
}
@inproceedings {wdhaes2004,
	title = {A highly optimized nonlinear least squares technique for sinusoidal analysis: From O(K^2N) to O(N log(N))},
	booktitle = {Proceedings of the 116th Audio Engineering Society Convention (AES)},
	year = {2004},
	month = {May},
	publisher = {Audio Engineering Society (AES)},
	organization = {Audio Engineering Society (AES)},
	address = {Berlin, Germany},
	author = {W. D{\textquoteright}haes}
}
@inproceedings {CampmverhoyealeemansPostnovBequeEyndenNuytsLauwersVerbruggenDebyzerBaekelandtClerckjsijbersLaereavdlinde2004,
	title = {In vivo multimodal imaging of a rat model for Parkinson{\textquoteright}s disease: high resolution micro-MRI, micro-SPECT and micro-CT},
	booktitle = {21th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology},
	year = {2004},
	pages = {22-23},
	address = {Copenhagen, Denmark},
	author = {N. Van Camp and Marleen Verhoye and Alexander Leemans and A. Postnov and Dirk Beque and J. Van den Eynden and Johan Nuyts and E. Lauwers and Alfons Verbruggen and Zeger Debyser and Veerle Baekelandt and N. De Clerck and Jan Sijbers and Koen Van Laere and Annemie Van Der Linden}
}
@inproceedings {mverhoyeGroofMeirTindemansaleemansavdlinde2004,
	title = {In vivo neuroanatomy of the songbird brain, visualized through diffusion tensor imaging},
	booktitle = {21th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology},
	year = {2004},
	pages = {161},
	address = {Copenhagen, Denmark},
	author = {Marleen Verhoye and G. De Groof and V. Van Meir and I. Tindemans and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {mverhoyeGroofMeirTindemansaleemansavdlinde2004,
	title = {In vivo visualization of the neuroanatomy and brain connectivity of starling brain through diffusion tensor imaging},
	booktitle = {34rd Annual Meeting of the Society for Neuroscience},
	year = {2004},
	address = {San Diego, USA},
	author = {Marleen Verhoye and G. De Groof and V. Van Meir and I. Tindemans and Alexander Leemans and Annemie Van Der Linden}
}
@inproceedings {pscheundjdriesen2004,
	title = {Least squares interband denoising of color and multispectral images},
	booktitle = {Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore},
	year = {2004},
	pages = {985-988},
	author = {Paul Scheunders and J. Driesen}
}
@article {jsijbersajdendek2004,
	title = {Maximum Likelihood estimation of signal amplitude and noise variance from MR data},
	journal = {Magnetic Resonance in Medicine},
	volume = {51},
	number = {3},
	year = {2004},
	pages = {586-594},
	doi = {10.1002/mrm.10728},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {jsijbersajdendek2004,
	title = {The performance of generalized likelihood ratio tests for complex functional MRI data in the presence of phase model misspecification},
	booktitle = {European Society of Magnetic Resonance in Medicine (ESMRMB)},
	year = {2004},
	month = {September},
	pages = {96},
	address = {Copenhagen, Denmark},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {KempeneerssdbackerDelalieuxSterckxDebruynCoppinpscheund2004,
	title = {Upscaling of spectroradiometer data for stress detection in orchards with remote sensing},
	booktitle = {SPIE Remote Sensing, Gran Canaria, 13-16 september},
	volume = {127},
	year = {2004},
	pages = {37-45},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Maspalomas, Spain},
	author = {Pieter Kempeneers and Steve De Backer and Stephanie Delalieux and S Sterckx and W. Debruyn and P. Coppin and Paul Scheunders},
	editor = {Manfred Owe, Guido D{\textquoteright}Urso, Ben T. Gouweleeuw, Anne M. Jochum}
}
@inproceedings {jdriesenpscheund2004,
	title = {Wavelet based Filter Array Demosaicking},
	booktitle = {Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore},
	year = {2004},
	pages = {3311-3314},
	author = {J. Driesen and Paul Scheunders}
}
@inproceedings {sdbackerKempeneersDebruynpscheund2004,
	title = {Wavelet Based Hyperspectral Data Analysis for Vegetation Stress Classification},
	booktitle = {Proc. of Advanced Concepts for Intelligent Vision Systems},
	year = {2004},
	pages = {387-391},
	address = {Brussels, Belgium},
	author = {Steve De Backer and Pieter Kempeneers and W. Debruyn and Paul Scheunders}
}
@inproceedings {wdhaesxrodet2003,
	title = {Discrete Cepstrum Coefficients as Perceptual Features},
	booktitle = {International Computer Music Conference (ICMC)},
	year = {2003},
	author = {W. D{\textquoteright}haes and X Rodet}
}
@inproceedings {WaarsingaleemansDayEderveendvandyckBuelensClerckSasovWeinans2003,
	title = {Effects of Growth and OVX in the Tibia of Individual Rats: an in-vivo Micro-CT Study},
	booktitle = {49th Annual Meeting - Orthopaedic Research Society},
	year = {2003},
	address = {New Orleans, LA, USA},
	author = {J. H. Waarsing and Alexander Leemans and J. Day and A. G. H. Ederveen and Dirk Van Dyck and E. Buelens and N. De Clerck and A. Sasov and H. Weinans}
}
@inproceedings {SterckxCoppinsdbackerDebruynKempeneersMeulemanNackaertsReusenpscheund2003,
	title = {Information extraction techniques for monitoring of stress symptoms in orchards},
	booktitle = {Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen},
	year = {2003},
	pages = {278-283},
	author = {S Sterckx and P. Coppin and Steve De Backer and W. Debruyn and Pieter Kempeneers and K. Meuleman and K. Nackaerts and I. Reusen and Paul Scheunders}
}
@inproceedings {jsijbersajdendek2003,
	title = {Mapping a polyhedron onto a sphere: application to Fourier descriptors},
	booktitle = {22nd Benelux Meeting on Systems and Control},
	year = {2003},
	month = {March},
	address = {Lommel, Belgium},
	author = {Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {ajdendekjsijbers2003,
	title = {Maximum Likelihood estimation of signal amplitude and noise variance},
	booktitle = {13th IFAC Symposium on System Identification (SYSID-2003)},
	year = {2003},
	month = {August},
	pages = {126-131},
	address = {Rotterdam, The Netherlands},
	author = {Arnold Jan den Dekker and Jan Sijbers}
}
@inproceedings {wdhaesxrodet2003,
	title = {A New Estimation Technique for Determining the Control Parameters of a physical model of a trumpet},
	booktitle = {6th International Conference on Digital Audio Effects (DAFx03), London, England},
	year = {2003},
	month = {September},
	author = {W. D{\textquoteright}haes and X Rodet}
}
@inproceedings {MeulemanCoppinsdbackerDebruynNackaertspscheundStercks2003,
	title = {Optimal hyperspectral indicators for stress detection in orchards},
	booktitle = {Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen},
	year = {2003},
	pages = {534-541},
	author = {K. Meuleman and P. Coppin and Steve De Backer and W. Debruyn and K. Nackaerts and Paul Scheunders and S Sterckx}
}
@article {wdhaesdvandyckxrodet2003,
	title = {PCA-based Branch and Bound Search Algorithms for Computing K Nearest Neighbors},
	journal = {Pattern Recognition Letters},
	volume = {24},
	year = {2003},
	pages = {1437-1451},
	author = {W. D{\textquoteright}haes and Dirk Van Dyck and X Rodet}
}
@inproceedings {KempeneerssdbackerDebruynpscheund2003,
	title = {Wavelet Based Feature Extraction for Hyperspectral Vegetation Monitoring},
	booktitle = {SPIE International Symposium on Remote Sensing, Image and Signal Processing for Remote Sensing IX},
	year = {2003},
	pages = {297-305},
	address = {Barcelona, Spain},
	author = {Pieter Kempeneers and Steve De Backer and W. Debruyn and Paul Scheunders},
	editor = {L. Bruzzone}
}
@inproceedings {wdhaesdvandyckxrodet2002,
	title = {Control Parameter Estimation for a Physical Model of a Trumpet Using Pattern Recognition},
	booktitle = {IEEE Workshop on Model Based Processing and Coding of Audio (MPCA), Leuven, Belgium},
	year = {2002},
	month = {November},
	author = {W. D{\textquoteright}haes and Dirk Van Dyck and X Rodet}
}
@inproceedings {wdhaesdvandyckxrodet2002,
	title = {An efficient branch and bound seach algorithm for computing K nearest neighbors in a multidimensional vector space},
	booktitle = {IEEE Advanced Concepts for Intelligent Vision Systems (ACIVS), Gent, Belgium},
	year = {2002},
	month = {September},
	author = {W. D{\textquoteright}haes and Dirk Van Dyck and X Rodet}
}
@inproceedings {wdhaesdvandyckxrodet2002,
	title = {An efficient branch and bound seach algorithm for computing K nearest neighbors in a multidimensional vector space},
	booktitle = {Signal Processing, Pattern Recognition and Applications (SPPRA), Crete, Greece},
	year = {2002},
	month = {June},
	author = {W. D{\textquoteright}haes and Dirk Van Dyck and X Rodet}
}
@article {Yusdbackerpscheund2002,
	title = {Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery},
	journal = {Pattern Recognition Letters},
	volume = {23},
	number = {1},
	year = {2002},
	pages = {183-190},
	author = {Shixin Yu and Steve De Backer and Paul Scheunders}
}
@inproceedings {wdhaesxrodet2002,
	title = {Physical Constraints for the Control of a Physical Model of a Trumpet},
	booktitle = {International Conference on Digital Audio Effects (DAFx), Hamburg, Germany},
	year = {2002},
	month = {September},
	author = {W. D{\textquoteright}haes and X Rodet}
}
@mastersthesis {1278,
	title = {Unsupervised Pattern Recognition - Dimensionality Reduction and Classification},
	year = {2002},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	author = {Steve De Backer}
}
@inproceedings {wdhaesxrodet2001,
	title = {Automatic Estimation of Control Parameters: An Instance-Based Learning Approach},
	booktitle = {International Computer Music Conference (ICMC), Havana, Cuba},
	year = {2001},
	month = {September},
	author = {W. D{\textquoteright}haes and X Rodet}
}
@article {pscheundsdbacker2001,
	title = {Fusion and merging of multispectral images using multiscale fundamental forms},
	journal = {Journal of the Optical Society of America A},
	volume = {18},
	number = {10},
	year = {2001},
	pages = {2468-2477},
	author = {Paul Scheunders and Steve De Backer}
}
@mastersthesis {1279,
	title = {Infotree - A study of its foundations},
	year = {2001},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	author = {Bart De Boeck}
}
@inproceedings {pscheundsdbacker2001,
	title = {Multispectral image fusion and merging using multiscale fundamental forms},
	booktitle = {Proc. ICIP01, IEEE International Conference on Image Processing},
	year = {2001},
	pages = {902-905},
	address = {Thessaloniki, Greece},
	author = {Paul Scheunders and Steve De Backer}
}
@article {sdbackerpscheund2001,
	title = {Texture segmentation by frequency-sensitive elliptical competitive learning},
	journal = {Image and Vision Computing},
	volume = {19},
	number = {9},
	year = {2001},
	pages = {639-648},
	author = {Steve De Backer and Paul Scheunders}
}
@inproceedings {mverhoyeMichielsjsijbersEelenPeetersAudekerkeDHoogheDeynavdlinde2000,
	title = {Changes during pentetrazol-induced epilepsy in rat recorded by simultaneous EEG/MRI at 7T},
	booktitle = {SPIE Medical Imaging},
	volume = {3978},
	year = {2000},
	month = {February},
	pages = {485-493},
	address = {San Diego, USA},
	author = {Marleen Verhoye and I. Michiels and Jan Sijbers and J. Eelen and Ron R Peeters and Johan Van Audekerke and R. Dhooghe and P.P. De Deyn and Annemie Van Der Linden},
	editor = {Chin-Tu Chen, Anne V. Clough}
}
@inproceedings {bdboeckpscheunddvandyck2000,
	title = {From inductive inference to the fundamental equations of measuerement},
	booktitle = {Proc. First International Conference on Complex Systems},
	year = {2000},
	pages = {115-122},
	publisher = {Perseus Books},
	organization = {Perseus Books},
	author = {Bart De Boeck and Paul Scheunders and Dirk Van Dyck},
	editor = {Y. Bar-Yam}
}
@inproceedings {Yupscheundsdbacker2000,
	title = {Genetic Feature selection combined with composite fuzzy nearest neighbor classifers for high-dimensional remote sensing data},
	booktitle = {Proc. IEEE Intern. Conf. on Systems, Man \& Cybernetics, October 8-11, Nashville,TN},
	year = {2000},
	pages = {1912-1916},
	author = {Shixin Yu and Paul Scheunders and Steve De Backer}
}
@inproceedings {Yusdbackerpscheund2000,
	title = {Genetic feature selection combined with fuzzy kNN for hyperspectral satellite imagery},
	booktitle = {Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International},
	year = {2000},
	pages = {702-704},
	author = {Shixin Yu and Steve De Backer and Paul Scheunders}
}
@inproceedings {Yusdbackerpscheund2000,
	title = {Genetic Feature Selection Combined with Fuzzy K-NN for Hyperspectral Satellite Imagery},
	booktitle = {Intelligent Techniques and Soft Computing in Nuclear Science and Engineering},
	year = {2000},
	pages = {281-288},
	publisher = {World Scientific},
	organization = {World Scientific},
	author = {Shixin Yu and Steve De Backer and Paul Scheunders},
	editor = {d. Ruan, H.A. Abderrahim, P. D{\textquoteright}Hondt, E. Kerre}
}
@article {ijtsangirtsangbdboeckdvandyck2000,
	title = {Scaling and critical probability for cluster size and lattice animals diversity on randomly occupied square lattices},
	journal = {Journal of Physics A: Mathematical and General},
	volume = {33},
	number = {14},
	year = {2000},
	pages = {2739-2754},
	author = {Ing Jyh Tsang and Ing Ren Tsang and Bart De Boeck and Dirk Van Dyck}
}
@inproceedings {VanhouttemverhoyePeetersjsijbersEelenDHoogheDeynavdlinde2000,
	title = {Simultaneously recording of EEG/fMRI to study neurophysiological changes in rat brain during pentetrazol induced epileptic seizures},
	booktitle = {Federation of European Neuroscience (FENS) Millennium Meeting},
	volume = {12},
	year = {2000},
	month = {June},
	pages = {107},
	address = {Brighton, UK},
	author = {Greetje Vanhoutte and Marleen Verhoye and Ron R Peeters and Jan Sijbers and J. Eelen and R. Dhooghe and P.P. De Deyn and Annemie Van Der Linden}
}
@article {jsijbersajdendekmverhoyeavdlindedvandyck1999,
	title = {Adaptive anisotropic noise filtering for magnitude MR data},
	journal = {Magnetic Resonance Imaging},
	volume = {17},
	number = {10},
	year = {1999},
	pages = {1533-1539},
	doi = {10.1016/S0730-725X(99)00088-0},
	author = {Jan Sijbers and Arnold Jan den Dekker and Marleen Verhoye and Annemie Van Der Linden and Dirk Van Dyck}
}
@inproceedings {jsijbersajdendekmverhoyeavdlindedvandyck1999,
	title = {Adaptive anisotropic noise filtering for magnitude MR data},
	booktitle = {Proceedings of SPIE Medical Imaging},
	volume = {3661},
	year = {1999},
	month = {February},
	pages = {1418-1425},
	address = {San Diego, USA},
	author = {Jan Sijbers and Arnold Jan den Dekker and Marleen Verhoye and Annemie Van Der Linden and Dirk Van Dyck},
	editor = {Kenneth M. Hanson}
}
@article {sdbackerpscheund1999,
	title = {A competitive elliptical clustering algorithm},
	journal = {Pattern Recognition Letters},
	volume = {20},
	number = {11},
	year = {1999},
	pages = {1141-1147},
	author = {Steve De Backer and Paul Scheunders}
}
@article {pscheundsdbacker1999,
	title = {High-dimensional clustering using frequency sensitive competitive learning},
	journal = {Pattern Recognition},
	volume = {32},
	number = {2},
	year = {1999},
	pages = {193-202},
	author = {Paul Scheunders and Steve De Backer}
}
@article {ajdendekjsijbersdvandyck1999,
	title = {How to optimize the design of a quantitative HREM experiment so as to attain the highest precision},
	journal = {Journal of Microscopy},
	volume = {194},
	number = {1},
	year = {1999},
	pages = {95-104},
	author = {Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@article {ebettensdvandyckajdendekjsijbersBos1999,
	title = {Model-based two-object resolution from observations having counting statistics},
	journal = {Ultramicroscopy},
	volume = {77},
	number = {1},
	year = {1999},
	pages = {37-48},
	doi = {https://doi.org/10.1016/S0304-3991(99)00006-6},
	author = {E. Bettens and Dirk Van Dyck and Arnold Jan den Dekker and Jan Sijbers and A. van den Bos}
}
@article {jsijbersajdendekeramandvandyck1999,
	title = {Parameter estimation from magnitude MR images},
	journal = {International Journal of Imaging Systems and Technology},
	volume = {10},
	number = {2},
	year = {1999},
	pages = {109-114},
	doi = {10.1002/(SICI)1098-1098(1999)10:2<109::AID-IMA2>3.0.CO;2-R},
	author = {Jan Sijbers and Arnold Jan den Dekker and Erik Raman and Dirk Van Dyck}
}
@inproceedings {ajdendekjsijbersdvandyck1999,
	title = {Quantitative HREM: viewpoints on resolution, precision, and experimental design},
	booktitle = {Acta Cryst. A55 Supplement, Abstract M11.OE.OO5},
	year = {1999},
	month = {August},
	address = {IUCR Glasgow, Scotland},
	author = {Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@inproceedings {MichielsjsijbersEelenmverhoyeDHoogheNagelsDeynavdlinde1999,
	title = {Simultaneous EEG and MRI in an animal model for generalized epilepsy induced in the MRI instrument},
	booktitle = {Third Meeting of the Belgian Society for Neuroscience},
	number = {25},
	year = {1999},
	month = {May},
	address = {Brussels, Belgium},
	author = {I. Michiels and Jan Sijbers and J. Eelen and Marleen Verhoye and R. Dhooghe and Guy Nagels and P.P. De Deyn and Annemie Van Der Linden}
}
@inproceedings {MichielsjsijbersEelenmverhoyeDHoogheNagelsDeynavdlinde1999,
	title = {Simultaneous EEG and MRI in an animal model for generalized epilepsy induced in the MRI instrument},
	booktitle = {16th annual meeting: Magnetic Resonance Materials in Physics, Biology, and Medicine},
	year = {1999},
	month = {September},
	address = {Sevilla, Spain},
	author = {I. Michiels and Jan Sijbers and J. Eelen and Marleen Verhoye and R. Dhooghe and Guy Nagels and P.P. De Deyn and Annemie Van Der Linden}
}
@inproceedings {sdbackerpscheund1999,
	title = {Texture segmentation by frequency-sensitive elliptical competitive learning},
	booktitle = {Proc. ICIAP99, International Conference on Image Analysis and Processing , Venice, Italy, september 27-29},
	year = {1999},
	pages = {64-69},
	author = {Steve De Backer and Paul Scheunders}
}
@article {dvandyckebettensjsijbersBeeckBosajdendekJansenZandbergen1999,
	title = {Towards quantitative structure determination through electron holographic methods},
	journal = {Materials Characterization},
	volume = {42},
	number = {4},
	year = {1999},
	pages = {265-281},
	doi = {https://doi.org/10.1016/S1044-5803(99)00020-0},
	author = {Dirk Van Dyck and E. Bettens and Jan Sijbers and M. Op de Beeck and A. van den Bos and Arnold Jan den Dekker and J. Jansen and H. Zandbergen}
}
@article {WeyngvdwouweKoprowskiDaeleDhaenepscheundJacobMarck1999,
	title = {Value of morphometry, texture analysis, densitometry and histometry in the differential diagnosis and prognosis of malignant mesothelioma},
	journal = {Journal of Pathology},
	volume = {4},
	number = {189},
	year = {1999},
	pages = {581-589},
	author = {Barbara Weyn and G. Van de Wouwer and M. Koprowski and A. Van Daele and K. Dhaene and Paul Scheunders and W. Jacob and E. Van Marck}
}
@inproceedings {dvandyckajdendekjsijbersebettens1998,
	title = {Dose Limited Resolution},
	booktitle = {Proceedings Microscopy and Microanalysis},
	volume = {2},
	number = {2},
	year = {1998},
	month = {July},
	pages = {802-803},
	address = {Atlanta, Georgia, U.S.A},
	author = {Dirk Van Dyck and Arnold Jan den Dekker and Jan Sijbers and E. Bettens}
}
@inproceedings {jsijbersajdendekdvandyckeraman1998,
	title = {Estimation of signal and noise from Rician distributed data},
	booktitle = {Proceedings of the IASTED International Conference on Signal Processing and Communications},
	year = {1998},
	month = {February},
	pages = {140-143},
	address = {Canary Islands, Spain},
	author = {Jan Sijbers and Arnold Jan den Dekker and Dirk Van Dyck and Erik Raman}
}
@article {jsijbersajdendekAudekerkemverhoyedvandyck1998,
	title = {Estimation of the noise in magnitude MR images},
	journal = {Magnetic Resonance Imaging},
	volume = {16},
	number = {1},
	year = {1998},
	pages = {87-90},
	doi = {10.1016/S0730-725X(97)00199-9},
	author = {Jan Sijbers and Arnold Jan den Dekker and Johan Van Audekerke and Marleen Verhoye and Dirk Van Dyck}
}
@inproceedings {ajdendekjsijbersdvandyck1998,
	title = {How to design an HREM experiment so as to attain the highest precision?},
	booktitle = {ICEM14: 14th International Congress on Electron Microscopy},
	volume = {1},
	year = {1998},
	month = {September},
	pages = {621-622},
	address = {Cancun, Mexico},
	author = {Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@inproceedings {AudekerkemverhoyejsijbersDeVoogdSmuldersNewmanavdlinde1998,
	title = {Imaging birds ... in a bird cage: In vivo MRI microscopy of the canary brain at 7T},
	booktitle = {Proceedings of International Society for Magnetic Resonance in Medicine: Sixth Annual Meeting},
	volume = {2},
	number = {2},
	year = {1998},
	month = {April},
	pages = {162-163},
	author = {Johan Van Audekerke and Marleen Verhoye and Jan Sijbers and T. J. DeVoogd and T. Smulders and S. W. Newman and Annemie Van Der Linden}
}
@article {FransenDhoogheCampmverhoyejsijbersReyniersSorianoKamiguchiWillemsenKoekoekZeeuwDeynavdlindeLemmonKooyWillems1998,
	title = {L1 knockout mice show dilated ventricles, vermis hypoplasia and impaired exploration patterns},
	journal = {Human Molecular Genetics},
	volume = {7},
	number = {6},
	year = {1998},
	pages = {999-1009},
	doi = {10.1093/hmg/7.6.999},
	author = {Erik Fransen and R. Dhooghe and G. Van Camp and Marleen Verhoye and Jan Sijbers and E. Reyniers and P. Soriano and H. Kamiguchi and R. Willemsen and K.E. Koekoek and C.I. De Zeeuw and P.P. De Deyn and Annemie Van Der Linden and V. Lemmon and R.F. Kooy and P. J. Willems}
}
@article {jsijbersajdendekpscheunddvandyck1998,
	title = {Maximum Likelihood estimation of Rician distribution parameters},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {17},
	number = {3},
	year = {1998},
	pages = {357-361},
	doi = {10.1109/42.712125},
	author = {Jan Sijbers and Arnold Jan den Dekker and Paul Scheunders and Dirk Van Dyck}
}
@inproceedings {ajdendekjsijbersmverhoyedvandyck1998,
	title = {Maximum Likelihood estimation of the signal component magnitude in phase contrast MR images},
	booktitle = {Proceedings of SPIE Medical Imaging},
	volume = {3338},
	year = {1998},
	month = {February},
	pages = {408-415},
	address = {San Diego, California, USA},
	author = {Arnold Jan den Dekker and Jan Sijbers and Marleen Verhoye and Dirk Van Dyck}
}
@article {sdbackerNaudpscheund1998,
	title = {Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction},
	journal = {Pattern Recognition Letters},
	volume = {19},
	year = {1998},
	pages = {711-720},
	author = {Steve De Backer and A. Naud and Paul Scheunders}
}
@article {pscheundsdbackerNaud1998,
	title = {Non-linear mapping for feature extraction},
	journal = {Lecture Notes in Computer Science},
	volume = {1451},
	year = {1998},
	pages = {823-830},
	author = {Paul Scheunders and Steve De Backer and A. Naud}
}
@inproceedings {jsijbersajdendekmverhoyedvandyck1998,
	title = {Optimal estimation of T2 maps from magnitude MR data},
	booktitle = {Proceedings of SPIE Medical Imaging},
	volume = {3338},
	year = {1998},
	month = {February},
	pages = {384-390},
	address = {San Diego, CA, USA},
	author = {Jan Sijbers and Arnold Jan den Dekker and Marleen Verhoye and Dirk Van Dyck},
	editor = {Kenneth M. Hanson}
}
@article {pjedrasijgarciabdboeckdvandyck1998,
	title = {Optimal filtering versus regularization methods in the Fourier precompensation based proximity neurocorrection in electron beam lithography},
	journal = {Microelectronic Engineering},
	volume = {41},
	year = {1998},
	pages = {195-198},
	author = {P. Jedrasik and J. Garcia and Bart De Boeck and Dirk Van Dyck}
}
@inproceedings {ajdendekjsijbersdvandyck1998,
	title = {Optimizing the design of an HREM experiment so as to attain the highest resolution},
	booktitle = {Proceedings of FEMMS98: Frontiers of Electron Microscopy in Material Science},
	year = {1998},
	month = {April},
	address = {Kloster Irsee, Germany},
	author = {Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@inproceedings {ajdendekjsijbersdvandyck1998,
	title = {Optimizing the setting of an electron microscope for highest resolution using statistical parameter estimation theory},
	booktitle = {Workshop: Towards Atomic Resolution Analysis 98},
	year = {1998},
	month = {September},
	address = {Port Ludlow, WA, U.S.A},
	author = {Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@inproceedings {ebettensajdendekjsijbersdvandyck1998,
	title = {Ultimate resolution in the framework of parameter estimation},
	booktitle = {IASTED International Conference - Signal and Image Processing (SIP{\textquoteright}98)},
	year = {1998},
	month = {October},
	pages = {229-233},
	address = {Las Vegas, Nevada, USA},
	author = {E. Bettens and Arnold Jan den Dekker and Jan Sijbers and Dirk Van Dyck}
}
@inproceedings {KooyReyniersDHoogheDeynavdlindemverhoyejsijbersOostraWillems1997,
	title = {Characterization of the Fragile X knockout mouse},
	booktitle = {Abstracts of the second annual meeting of the Belgian society of neuroscience},
	year = {1997},
	month = {May},
	address = {Brussels, Belgium},
	author = {R.F. Kooy and E. Reyniers and R. Dhooghe and P.P. De Deyn and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers and B. A. Oostra and P. J. Willems}
}
@article {dvandyckebettensjsijbersBeeckajdendekBos1997,
	title = {From High Resolution Image to Atomic Structure: how fare are we?},
	journal = {Scanning Microscopy, Special Issue on Image Processing},
	volume = {11},
	year = {1997},
	note = {ISSN: 0891-7035},
	pages = {467-478},
	author = {Dirk Van Dyck and E. Bettens and Jan Sijbers and M. Op de Beeck and Arnold Jan den Dekker and A. van den Bos}
}
@inproceedings {pscheundsdbacker1997,
	title = {Joint quantization and error-diffusion of color images using competitive learning},
	booktitle = {Proc. IEEE Conference on Image Processing , Santa Barbara, 26-29 october},
	year = {1997},
	pages = {811-814},
	author = {Paul Scheunders and Steve De Backer}
}
@article {denDekker:97,
	title = {Resolution: a survey},
	journal = {J. Opt. Soc. Am. A},
	volume = {14},
	number = {3},
	year = {1997},
	month = {Mar},
	pages = {547{\textendash}557},
	publisher = {OSA},
	abstract = {Past and present approaches to the concept of optical resolution are reviewed.},
	doi = {10.1364/JOSAA.14.000547},
	url = {http://josaa.osa.org/abstract.cfm?URI=josaa-14-3-547},
	author = {Arnold Jan den Dekker and A. van den Bos}
}
@inbook {dvandyckebettensjsijbersajdendekBosBeeckJansenZandbergen1997,
	title = {Resolving atoms: what do we have? what do we want?},
	booktitle = {Institute of Physics Conference Series},
	volume = {153},
	number = {3},
	year = {1997},
	month = {December},
	pages = {95-100},
	publisher = {Institute of Physics Ltd},
	organization = {Institute of Physics Ltd},
	address = {Cambridge, UK},
	author = {Dirk Van Dyck and E. Bettens and Jan Sijbers and Arnold Jan den Dekker and A. van den Bos and M. Op de Beeck and J. Jansen and H. Zandbergen},
	editor = {J. M. Rodenburg}
}
@inproceedings {jsijbersajdendekpscheunderamandvandyck1997,
	title = {Unbiased signal estimation in magnitude MR images},
	booktitle = {Proceedings of the European Society for Magnetic Resonance in Medicine and Biology},
	volume = {2},
	number = {2},
	year = {1997},
	month = {September},
	pages = {174},
	address = {Brussels, Belgium},
	author = {Jan Sijbers and Arnold Jan den Dekker and Paul Scheunders and Erik Raman and Dirk Van Dyck}
}
@inproceedings {dmeersmpscheunddvandyck1996,
	title = {Detection of microcalcifications using neural networks},
	booktitle = {Digital Mammography},
	series = {ICS},
	year = {1996},
	pages = {287-290},
	author = {D. Meersman and Paul Scheunders and Dirk Van Dyck},
	editor = {K. Doi}
}
@article {pscheundClerckWille1994,
	title = {Computerized image storage and analysis of contracting cardiac myocytes},
	journal = {Journal of Computer Assisted Microscopy},
	volume = {6},
	number = {2},
	year = {1994},
	pages = {77-83},
	author = {Paul Scheunders and N. De Clerck and J. Wille}
}
