@article {2472, title = {Anatomical exploration of Vipera ammodytes (family Viperidae) horn supports cephalic appendage sensory function in non-aquatic snakes}, journal = {Journal of Anatomy}, year = {2026}, abstract = {Several snakes possess cephalic appendages over their eyes and snouts, but their exact function remains largely unknown. In one aquatic species, such structures have been associated with a mechanosensory role, and this suggests that other horned snakes may have evolved analogous appendages. To be considered sensory structures, cephalic appendages should be highly innervated by specific cranial nerves like the trigeminal, and perhaps carry specialised integumentary sense organs. The identification of trigeminal branches reaching the cephalic appendages would be consistent with sensory capability of the structures. Here we tested whether the rostral appendage of the nose-horned viper (Vipera ammodytes) could serve such a sensory function. We conducted an integrative anatomical exploration of the species{\textquoteright} head and appendage using a combination of diffusible iodine-based contrast-enhanced micro computed tomography, classical histology and scanning electron microscopy and found support for our initial hypothesis. The rostral appendage of V. ammodytes is highly innervated by the ophthalmic branch of the trigeminal nerve, and we also found dermal sensory organs over the snake{\textquoteright} snout and appendage scales. These findings suggest that a sensory function for cephalic appendages could also be possible in non-aquatic species, hinting that more analogous sensory structures may have evolved across horned snakes and other reptile groups.}, keywords = {cranial nerves, diceCT, functional morphology, histology, mechanosensation, SEM, sense organs, sensory ecology, trigeminal}, doi = {10.1111/joa.70132}, url = {https://onlinelibrary.wiley.com/doi/10.1111/joa.70132}, author = {Federico Banfi and Paul M. Gignac and Tom Hellebuyck and Joaquim G. Sanctorum and Barbara De Kegel and Dominique Adriaens and Raoul Van Damme} } @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 {2439, title = {Spatio-temporal characterization of gastric distensibility in upper endoscopy identifies the presence of Helicobacter pylori}, journal = {IEEE Transactions on Medical Imaging}, year = {2026}, pages = {1-1}, abstract = {Assessment of gastric distensibility is crucial for understanding various gastrointestinal disorders, particularly those affecting gastric motility and reflux conditions. Gastric distensibility can be altered by pathological conditions such as linitis plastica or gastric mucosal inflammation, as seen in Helicobacter pylori infections. Although distensibility is evaluated during routine endoscopy, the assessment remains purely visual. Moreover, some specialized endoscopic tools assess only specific gastric regions and are often unavailable. Artificial intelligence tools may used to estimate the gastric three-dimensional surface from the endoscopy video and capture temporal distensibility changes of the gastric surface. This paper introduces a novel spatio-temporal characterization of the gastric distensibility during a routine endoscopy procedure. The method reconstructs the gastric surface for each frame of a short endoscopy video using a shape-from- shading network trained with a synthetic endoscopy collection. Local and regional changes in surface bending are then quantified, which herein depend on the distensibility. This spatio-temporal characterization was applied to a group of 160 patients, among them 60 diagnosed with Helicobacter pylori confirmed by pathology examination. The obtained characteristics in three different regions: body, antrum, and pylorus, demonstrated significant differences between patients with and without Helicobacter pylori under a t-test (p < 0.05). The proposed method effectively captures subtle gastric wall bending from routine endoscopy videos, providing a strategy for analyzing distensibility in pathological conditions across various gastric regions without requiring specialized tools.}, keywords = {Bending, Cameras, Endoscopes, Endoscopy, Gastric distensibility, Gastroenterology, Helicobacter pylori, image reconstruction, Protocols, Spatio-temporal characterization, Stomach, Surface reconstruction, Three-dimensional displays, Three-dimensional reconstruction, Videos}, doi = {10.1109/TMI.2026.3672198}, author = {Ruano-Balseca, Josu{\'e} and Bravo, Diego and Diana Giraldo and G{\'o}mez, Mart{\'\i}n and Gonzalez, Fabio A. and Romero, Eduardo} } @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 {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.} } @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 {2351, title = {Deep Learning-Enhanced Accelerated 2D TSE and 3D Super-Resolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment}, journal = {Investigative Radiology}, volume = {60}, year = {2025}, pages = {220-233}, doi = {10.1097/RLI.0000000000001118}, author = {C{\'e}line Smekens and Quinten Beirinckx and Frederik Bosmans and Floris Vanhevel and Annemie Snoeckx and Jan Sijbers and Ben Jeurissen and Thomas Janssens and Pieter Van Dyck} } @inproceedings {2391, title = {Dual Domain Swin Transformer based Reconstruction method for Sparse-View Computed Tomography}, booktitle = {iCT 2025 - 14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium}, year = {2025}, doi = {doi.org/10.58286/30751}, author = {Jonas Van der Rauwelaert and Caroline Bossuyt and Jan Sijbers} } @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 C{\'e}line 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 {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} } @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 {2422, title = {Soil Moisture Content Estimation From Hyperspectral Remote Sensing Data}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, volume = {18}, year = {2025}, pages = {22231-22240}, abstract = {Because of its significant absorption power, especially in the shortwave infrared optical region, water dominates the optical reflectance properties of water-bearing materials. This allows us to study a material{\textquoteright}s water-related features, such as its moisture content, from optical reflectance. In this study, we proposed a framework to estimate soil moisture content from PRISMA hyperspectral remote sensing data. The proposed framework requires a dry endmember spectrum and an endmember spectrum of high soil moisture along with ground truth moisture content, obtained from ground measurements. The method takes into account the complex interaction of light with soils, the large variation of environmental conditions, leading to spectral variability and the soil-specific behavior of water. The framework is extensively validated using ground-measured soil moisture data from the International Soil Moisture Network database. A total of 1418 PRISMA images corresponding to 151 ground stations were analyzed. From 518 retained images, a total root-mean-squared error of 8.682 \% and R2 of 0.385 was obtained.}, keywords = {Absorption, Hyperspectral, Hyperspectral imaging, Land surface, Machine learning regression, Optical imaging, Optical reflection, Optical sensors, PRISMA, Reflectivity, remote sensing, Soil measurements, Soil moisture, soil moisture content (SMC), vegetation mapping}, doi = {10.1109/JSTARS.2025.3603841}, author = {Jambhali, Ketaki Vinay and Koirala, Bikram and Bnoulkacem, Zakaria and Paul Scheunders} } @article {2411, title = {SwinIR-based Dual-Domain Reconstruction for Sparse-View Computed Tomography}, journal = {Journal of Nondestructive Evaluation}, volume = {44}, year = {2025}, doi = {https://doi.org/10.1007/s10921-025-01244-3}, author = {Jonas Van der Rauwelaert and Caroline Bossuyt and Stijn Verleden and Jan Sijbers} } @mastersthesis {2330, title = {Automating the planning of transcatheter Mitral Valve Interventions}, volume = {Engineering Science}, year = {2024}, type = {PhD thesis}, author = {Lopes, Patricia} } @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 {2459, title = {Diffusion MRI marks progressive alterations in fiber integrity in the zQ175DN mouse model of Huntington{\textquoteright}s disease}, journal = {Neurobiology of Disease}, volume = {193}, year = {2024}, month = {Jan-04-2024}, pages = {106438}, issn = {09699961}, doi = {10.1016/j.nbd.2024.106438}, author = {Vidas-Guscic, Nicholas and van Rijswijk, Jo{\"e}lle and Van Audekerke, Johan and Ben Jeurissen and Nnah, Israel and Tang, Haiying and Mu{\~n}oz-Sanjuan, Ignacio and Pustina, Dorian and Cachope, Roger and Van der Linden, Annemie and Bertoglio, Daniele and Verhoye, Marleen} } @inproceedings {2440, title = {Estimating Polyp Size From a Single Colonoscopy Image Using a Shape-From-Shading Model}, booktitle = {2024 IEEE International Symposium on Biomedical Imaging (ISBI)}, year = {2024}, pages = {1-5}, keywords = {Accuracy, Colonoscopy, Depth estimation, image segmentation, polyp size estimation, Solid modeling, Surface reconstruction, Surveillance, Synthetic database, Three-dimensional displays}, doi = {10.1109/ISBI56570.2024.10635358}, author = {Ruano-Balseca, Josu{\'e} and Bravo, Diego and Diana Giraldo and G{\'o}mez, Mart{\'\i}n and Gonzalez, Fabio A. and Manzanera, Antoine and Romero, Eduardo} } @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} } @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} } @inproceedings {2397, title = {Improving Spectral Unmixing Performance by Frequency Component Reduction}, booktitle = {2024 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)}, year = {2024}, pages = {1-5}, keywords = {Fast Fourier Transform, Fast Fourier transforms, Genetic algorithms, Hyperspectral, Hyperspectral imaging, intimate mixtures, Noise, Noise level, Redundancy, Robustness, Signal processing algorithms, Stability analysis, Surface treatment, unmixing}, doi = {10.1109/WHISPERS65427.2024.10876530}, author = {Bnoulkacem, Zakaria and Koirala, Bikram and Paul Scheunders} } @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} } @article {2361, title = {Nonlinear Spectral Unmixing Using B{\'e}zier Surfaces}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {62}, year = {2024}, pages = {1-16}, keywords = {B{\'e}zier surface, Data models, Hyperspectral, Hyperspectral imaging, Manifolds, mineral powder mixtures, mixing models, nonlinearity, Reflectivity, Sensor phenomena and characterization, spectral variability, Surface treatment, Training}, doi = {10.1109/TGRS.2024.3422495}, author = {Koirala, Bikram and Rasti, Behnood and Bnoulkacem, Zakaria and Paul Scheunders} } @mastersthesis {2356, title = {Technological breakthroughs towards motion-robust super-resolution quantitative magnetic resonance imaging for improved detection of brain diseases}, year = {2024}, month = {07/2024}, pages = {268}, school = {University of Antwerp}, type = {PhD Thesis}, abstract = {Magnetic resonance imaging (MRI) is one of the most widely used neuroimaging techniques, thanks to its exceptional soft tissue contrast and intrinsic safety for patients. Unfortunately, signal intensities in conventional MRI images are expressed in relative units that depend on scanner hardware and software. While this poses no issue for visual inspection of anatomy, it complicates the quantitative comparison of signal intensities within a scan, between successive scans, and among different subjects. In contrast, quantitative MRI (qMRI) generates quantitative maps of absolute biophysical tissue parameters by voxel-wise fitting a biophysical signal model to a series of contrast-weighted scans. Increasing evidence suggests that qMRI can detect and quantify subtle microscopic tissue damage, aiding in the early detection and accurate diagnosis of various neurodegenerative diseases such as Alzheimer{\textquoteright}s or multiple sclerosis. The impact of these diseases is growing in our rapidly aging society. However, current qMRI techniques require long scan times due to the need for multiple contrast-weighted scans with high-resolution and high signal-to-noise ratio (SNR). Long scan times increase the risk of motion artifacts, reduce patient throughput, and decrease patient comfort, hindering the clinical adoption of qMRI. This work therefore investigates the use of model-based super-resolution reconstruction (SRR) for qMRI, aiming to optimize the trade-off between spatial resolution, SNR, and scan time. SRR enables the reconstruction of a high-resolution scan or parameter map from a series of low-resolution MRI scans, with typically shorter scan time per image. As an additional innovation in this thesis, patient movement is jointly estimated, which is crucial to avoid motion artifacts in the reconstruction. The new SRR framework is extensively tested and compared with existing SRR methods, both in computer simulations and using real brain MRI data. Furthermore, the new framework uses Bayesian statistics to incorporate prior knowledge about noise and brain tissue characteristics into the reconstruction process. This allows for the reconstruction of a 3D high-resolution quantitative tissue parameter map from motion-affected low-resolution MRI scans. Application to real brain MRI shows that the proposed framework significantly improves the accuracy of tissue parameter quantification compared to methods with a separate motion correction step. Finally, the SRR framework is extended to perfusion MRI for improved quantification of cerebral blood flow (CBF), in combination with Arterial Spin Labeling (ASL). As a result, a high-resolution quantitative CBF parameter map can be directly reconstructed from low-resolution ASL MRI scans, significantly improving SNR and CBF accuracy over traditional ASL methods.}, doi = {10.63028/10067/2069070151162165141}, url = {https://repository.uantwerpen.be/desktop/irua}, author = {Quinten Beirinckx} } @conference {2291, title = {Accelerated Dual-contrast Three-dimensional Knee Magnetic Resonance Imaging Using Super-resolution Reconstructed Deep Learning-enhanced Two-dimensional Dixon Turbo Spin-echo Imaging}, volume = {27}, year = {2023}, month = {05/2023}, pages = {1-24}, publisher = {Thieme Medical Publishers, Inc.}, abstract = {Recent work on three-dimensional (3D) super-resolution reconstruction (SRR) of conventional two-dimensional (2D) turbo spin-echo (TSE) knee magnetic resonance imaging (MRI) shows that high-resolution isotropic knee MRI is technically feasible. Yet the use of acceleration techniques and contrast optimization are needed for clinical validation of this 3D method. With the advent of deep learning (DL) image reconstruction techniques, high acceleration of SRR input data is now achievable through extended use of simultaneous multislice and parallel imaging methods. Moreover, the combination of accelerated TSE with the Dixon method allows us to acquire fat-suppressed and non-fat-suppressed data within a single acquisition that further accelerates the dual-contrast SRR protocol. This study evaluated the technical feasibility of 3D SRR MRI based on DL-enhanced highly accelerated 2D Dixon TSE MRI. It also compared image quality and diagnostic confidence of this dual-contrast 3D technique to (accelerated) conventional 2D TSE knee MRI. We hypothesized that the SRR method provides the required contrasts needed for comprehensive knee joint evaluation in a competitive acquisition time.}, doi = {10.1055/s-0043-1770025}, url = {https://www.thieme-connect.com/products/ejournals/abstract/10.1055/s-0043-1770025}, author = {C{\'e}line Smekens and Floris Vanhevel and Quinten Beirinckx and Thomas Janssens and Pieter Van Dyck} } @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 {2335, title = {Corrosion detection using hyperspectral VNIR and SWIR imaging for drone-based inspection of electrical pylons}, booktitle = {EUROCORR 2023, European Corrosion Congress, Proceedings}, year = {2023}, pages = {2}, author = {Bnoulkacem, Zakaria and Vlaminck, Michiel and Luzardo Morocho, Gonzalo Raimundo and Zivariadab, Hamed and Zahiri, Zohreh and Koirala, Bikram and Platisa, Ljiljana and Luong, Hiep and Paul Scheunders and Mangialetto, Fr{\'e}d{\'e}ric and Bufi, Irid} } @inproceedings {2334, title = {Drone-Based Corrosion Detection on High-Voltage Transmission Towers Using Hyperspectral Imaging}, booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)}, year = {2023}, pages = {1-5}, keywords = {Corrosion, corrosion detection, Drones, High-voltage techniques, high-voltage tower, Hyperspectral imaging, Inspection, Pipelines, Poles and towers, UAV}, doi = {10.1109/WHISPERS61460.2023.10431111}, author = {Vlaminck, Michiel and Bnoulkacem, Zakaria and Luzardo, Gonzalo and Zivariadab, Hamed and Zahiri, Zohreh and Koirala, Bikram and Mangialetto, Fr{\'e}d{\'e}ric and Bufi, Irid and Platisa, Ljiljana and Jayapala, Murali and Paul Scheunders and Luong, Hiep} } @conference {2300, title = {Exploring the Correlation between Disability Status and Brain Volumetric Measurements Using Real-World Retrospective Magnetic Resonance Images in People with Multiple Sclerosis}, number = {1637}, year = {2023}, address = {October 11-13, Milan, Italy}, abstract = {This study investigated whether retrospective real-world MR image databases can be used to obtain MR-based biomarkers of multiple sclerosis (MS) disability by examining correlations between Expanded Disability Status Scale (EDSS) scores and volumetric measurements from reconstructed T2-weighted fluid-attenuated inversion recovery (FLAIR) in people with MS (PwMS).}, author = {Hamza Khan and Diana Giraldo and Quinten Beirinckx and Jan Sijbers and Philippe Lambin and Henry C. Woodruff and Liesbet M. Peeters} } @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 {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} } @inproceedings {2331, title = {Soil Moisture Content Estimation from Hyperspectral Remote Sensing Data}, booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)}, year = {2023}, pages = {1-5}, keywords = {Hyperion EO-1, Hyperspectral, Hyperspectral imaging, machine learning, Moisture, Optical reflection, Optical saturation, Optical sensors, Optical signal processing, remote sensing, Soil moisture, soil moisture content}, doi = {10.1109/WHISPERS61460.2023.10431194}, author = {Jambhali, Ketaki Vinay and Koirala, Bikram and Bnoulkacem, Zakaria and Paul Scheunders} } @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 {2285, title = {Towards material and process agnostic features for the classification of pore types in metal additive manufacturing}, journal = {Materials \& Design}, volume = {227}, year = {2023}, pages = {111757}, doi = {10.1016/j.matdes.2023.111757}, author = {M. Vandecasteele and R. Heylen and Domenico Iuso and A. Thanki and W. Philips and A. Witvrouw and D. Verhees and B. G. Booth} } @inproceedings {2332, title = {Unmixing Intimate Mixtures Using B{\'e}zier Surfaces}, booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)}, year = {2023}, pages = {1-5}, keywords = {hyperspectral image, Hyperspectral imaging, intimate mixtures, Lighting, nonlinear unmixing, Reflectivity, Signal processing, Surface reconstruction, Surface treatment, Training}, doi = {10.1109/WHISPERS61460.2023.10431306}, author = {Koirala, Bikram and Rasti, Behnood and Bnoulkacem, Zakaria and Paul Scheunders} } @article {2219, title = {Using particle systems for mitral valve segmentation from 3D transoesophageal echocardiography (3D TOE) - a proof of concept}, journal = {Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization}, volume = {11}, year = {2023}, pages = {112-120}, doi = {10.1080/21681163.2022.2058416}, url = {https://doi.org/10.1080/21681163.2022.2058416}, author = {Patricia Lopes and Paul Van Herck and Eefje Verhoelst and Roel Wirix-Speetjens and Jan Sijbers and Johan Bosmans and Jos Vander Sloten} } @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} } @article {2273, title = {Automated Mitral Valve Assessment for Transcatheter Mitral Valve Replacement (TMVR) Planning}, journal = {Frontiers in Bioengineering and Biotechnology}, volume = {16}, year = {2022}, pages = {1-13}, doi = {https://doi.org/10.3389/fbioe.2022.1033713}, author = {Lopes, Patricia and Paul Van Herck and J. Ooms and N. Van Mieghem and Wirix-Speetjens, Roel and Jan Sijbers and Vander Sloten, Jos and Bosmans, Johan} } @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 {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 {2209, title = {Evaluation of a Morphable Anthropomorphic Articulated Total Body Model}, booktitle = {Design Tools and Methods in Industrial Engineering II - Proceedings of the 2nd International Conference on Design Tools and Methods in Industrial Engineering, ADM 2021}, year = {2022}, pages = {761{\textendash}772}, publisher = {Springer}, organization = {Springer}, abstract = {In this work a new approach for the creation of Articulated Total Body (ATB) models for person-specific multi-body simulations is presented, with the main aim of overcoming limitations related to classical multi-ellipsoids ATB models, based on regression equations having only the weight and the height of the subject as input. The new methodology is based on a Statistical Shape Model (SSM), morphable according to up to 24 input parameters: the SSM was obtained from Principal Component Analysis (PCA), applied on a wide database of 3D human scans (CAESAR). The so obtained geometry can be segmented automatically to generate body segments with the respective inertial properties (mass, principal moments of inertia, and centres of mass location). The routine has been tested on a random set of 20 male subjects and the classical multi-ellipsoids models were compared to these in terms of inertial properties and 3D external geometry: the highest differences were registered at the abdomen and the thighs for what concerns the mass (60\%), principal moments (75\%) and centres of mass (50 mm) properties; the trunk, the shoulder and the calves are the most critical areas for the external geometry (average distance between the anthropomorphic and ellipsoids models equal to 50 mm). A contribution has been made to build person-specific multibody models. This is a valuable method since approximations made by multi-ellipsoidal models have resulted to be relevant at specific body areas, and personalised models can be a support to design and to forensic analyses.}, keywords = {3D parametric human model, Articulated total body, Forensic biomechanics, Multibody analysis, principal component analysis (PCA)}, isbn = {978-3-030-91233-8}, doi = {10.1007/978-3-030-91234-5_77}, author = {Giulia Pascoletti and Toon Huysmans and Paolo Conti and Zanetti, Elisabetta M.}, editor = {Caterina Rizzi and Francesca Campana and Michele Bici and Francesco Gherardini and Tommaso Ingrassia and Paolo Cicconi} } @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} } @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} } @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} } @mastersthesis {2271, title = {Quantitative assessment of 3D foot shape using statistical shape analysis}, volume = {PhD in Sciences}, year = {2022}, month = {10/2022}, type = {PhD thesis}, author = {Kristina Stankovi{\'c}} } @article {2248, title = {Self-calibration of C-arm imaging system using interventional instruments during an intracranial biplane angiography.}, journal = {Int J Comput Assist Radiol Surg}, year = {2022}, month = {2022 Mar 12}, abstract = {To create an accurate 3D reconstruction of the vascular trees, it is necessary to know the exact geometrical parameters of the angiographic imaging system. Many previous studies used vascular structures to estimate the system{\textquoteright}s exact geometry. However, utilizing interventional devices and their relative features may be less challenging, as they are unique in different views. We present a semi-automatic self-calibration approach considering the markers attached to the interventional instruments to estimate the accurate geometry of a biplane X-ray angiography system for neuroradiologic use.

METHODS: A novel approach is proposed to detect and segment the markers using machine learning classification, a combination of support vector machine and boosted tree. Then, these markers are considered as reference points to optimize the acquisition geometry iteratively.

RESULTS: The method is evaluated on four clinical datasets and three pairs of phantom angiograms. The mean and standard deviation of backprojection error for the catheter or guidewire before and after self-calibration are [Formula: see text]~mm and [Formula: see text]~mm, respectively. The mean and standard deviation of the 3D root-mean-square error (RMSE) for some markers in the phantom reduced from [Formula: see text] to [Formula: see text]~mm.

CONCLUSION: A semi-automatic approach to estimate the accurate geometry of the C-arm system was presented. Results show the reduction in the 2D backprojection error as well as the 3D RMSE after using our proposed self-calibration technique. This approach is essential for 3D reconstruction of the vascular trees or post-processing techniques of angiography systems that rely on accurate geometry parameters.}, issn = {1861-6429}, doi = {10.1007/s11548-022-02580-9}, author = {Chabi, Negar and Domenico Iuso and Beuing, Oliver and Preim, Bernhard and Saalfeld, Sylvia} } @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 sqstm1tmĪ”UBA 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 C{\'e}line Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @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 {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 C{\'e}line Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @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} } @article {2049, title = {Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study}, journal = {Journal of Orthopaedic Research }, volume = {39}, year = {2021}, pages = {1318{\textendash}1330}, doi = {10.1002/jor.24684}, author = {Pieter Van Dyck and Martijn Froeling and Christiaan H.W. Heusdens and Jan Sijbers and Annemie Ribbens and Thibo Billiet} } @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} } @conference {2205, title = {High-resolution T2* mapping of the knee based on UTE Spiral VIBE MRI}, volume = {34}, year = {2021}, pages = {S53-S54}, author = {C{\'e}line 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} } @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} } @article {2095, title = {Outlier detection for foot complaint diagnosis: modeling confounding factors using metric learning}, journal = {IEEE Intelligent Systems}, volume = {36}, year = {2021}, pages = {41-49}, doi = {10.1109/MIS.2020.3046431}, author = {Brian G. Booth and No{\"e}l L.W. Keijsers and Jan Sijbers} } @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} } @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} } @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 C{\'e}line 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} } @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 = {C{\'e}line 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} } @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 {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} } @article {2032, title = {Co valence transformation in isopolar LaCoO3/LaTiO3 perovskite heterostructures via interfacial engineering}, journal = {Phys. Rev. Materials}, volume = {4}, year = {2020}, chapter = {026001}, doi = {https://doi.org/10.1103/PhysRevMaterials.4.026001}, author = {G Araizi-Kanoutas and J Geessinck and N Gauquelin and S Smit and X H Verbeeck and S K Mishra and P Bencok and C Schlueter and T-L Lee and D Krishnan and J Fatermans and Jo Verbeeck and G Rijnders and G Koster and M S Golden} } @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 {2058, title = {Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets}, journal = {Science Direct Elsevier Neural Networks}, volume = {121}, year = {2020}, month = {01/2020}, pages = {101-121}, chapter = {101-121}, doi = {https://doi.org/10.1016/j.neunet.2019.07.020}, url = {https://www.sciencedirect.com/science/article/pii/S0893608019302163?via\%3Dihub$\#$!}, author = {Viktor Varkarakis and Shabab Bazrafkan and Peter Corcoran} } @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 {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} } @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} } @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 {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 {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} } @article {2017, title = {PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping}, journal = {PlosOne}, volume = {15}, year = {2020}, pages = {e0229685}, doi = {https://doi.org/10.1371/journal.pone.0229685}, author = {Brian G Booth and Eva Hoefnagels and Toon Huysmans and Jan Sijbers and No{\"e}l L.W. Keijsers} } @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} } @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 {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 {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 {2076, title = {Unveiling Water Dynamics in Fuel Cells from Time-Resolved Tomographic Microscopy Data}, journal = {Scientific Reports}, volume = {10}, year = {2020}, doi = {https://doi.org/10.1038/s41598-020-73036-w}, author = {Minna B{\"u}hrer and Hong Xu and Jens Eller and Jan Sijbers and Marco Stampanoni and Federica Marone} } @conference {1924, title = {Advancing Analysis Techniques for Plantar Pressure Videos via Open-Access Contributions}, year = {2019}, author = {Brian G Booth and No{\"e}l L.W. Keijsers and Toon Huysmans and Jan Sijbers} } @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.} } @article {1927, title = {An assessment of the information lost when applying data reduction techniques to dynamic plantar pressure measurements}, journal = {Journal of Biomechanics }, volume = {87}, year = {2019}, pages = {161-166}, doi = {https://doi.org/10.1016/j.jbiomech.2019.02.008}, author = {Brian G Booth and No{\"e}l L.W. Keijsers and Jan Sijbers and Toon Huysmans} } @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} } @inproceedings {1966, title = {A Deep Learning Approach to Horse Bone Segmentation from Digitally Reconstructed Radiographs}, booktitle = {International Conference on Image Processing Theory, Tools, and Applications}, year = {2019}, doi = {10.1109/IPTA.2019.8936082}, author = {Jeroen Van Houtte and Shabab Bazrafkan and Filip Vandenberghe and Guoyan Zheng and Jan Sijbers} } @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} } @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} } @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 (Ī”=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} } @article {1991, title = {Importance of pressure plasticity during compression of probiotic tablet formulations}, journal = {European Journal of Pharmaceutics and Biopharmaceutics}, volume = {145}, year = {2019}, pages = {7-11}, doi = {https://doi.org/10.1016/j.ejpb.2019.10.001}, author = {E Byl and Piet Bladt and S Lebeer and Filip Kiekens} } @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} } @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} } @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} } @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 {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} } @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} } @proceedings {1899, title = {ACIVS 2018, Advanced Concepts for Intelligent Vision Systems }, volume = {11182}, year = {2018}, author = {J Blanc-Talon and D Helbert and Wilfried Philips and D Popescu and Paul Scheunders} } @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} } @inproceedings {1933, title = {Capturing Joint Angles of the Off-Site Human Body}, booktitle = {IEEE Sensors 2018}, year = {2018}, pages = {1{\textendash}4}, publisher = {IEEE}, organization = {IEEE}, address = {United States}, abstract = {Motion capture (mocap) is traditionally conducted by optical systems. These are expensive and usually limited to controlled environments. We investigated the accuracy of portable and inexpensive mocap sensor systems compared to benchmark optical systems with respect to tracking joint angles. This review summarizes the findings of 21 studies. In these studies, 228 subjects were employed, and 16 joints were tracked, spanning a range of activities. We did not find a system that is consistent and equally accurate across all joint angles for all activities (root mean square error up to 12.1 degrees). However, under some ideal conditions, the results are on par with optical mocap. Our recommendations for future research and development are to focus on tracking faster activities, activities in off-site conditions, and following standardized biomechanical models of joint angles.}, keywords = {IMU, joint kinematics, motion capture, off-site, wearable}, isbn = {978-1-5386-4708-0}, doi = {10.1109/ICSENS.2018.8589711}, author = {Raman Garimella and Thomas Peeters and Koen Beyers and Steven Truijen and Toon Huysmans and Stijn Verwulgen} } @article {1817, title = {Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid Ī²-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} } @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} } @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} } @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} } @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 {1837, title = {STAPP: SpatioTemporal Analysis of Plantar Pressure Measurements using Statistical Parametric Mapping}, journal = {Gait and Posture}, volume = {3}, year = {2018}, pages = {268-275}, abstract = {Background: Pedobarography produces large sets of plantar pressure samples that are routinely subsampled (e.g. using regions of interest) or aggregated (e.g. center of pressure trajectories, peak pressure images) in order to simplify statistical analysis and provide intuitive clinical measures. Research Question: We hypothesize that these data reductions discard gait information that can be used to differentiate between groups or conditions. Methods: To test the hypothesis of null information loss, we created an implementation of statistical parametric mapping (SPM) for dynamic plantar pressure datasets (i.e. plantar pressure videos). Our SPM software framework brings all plantar pressure videos into anatomical and temporal correspondence, then performs statistical tests at each sampling location in space and time. Novelly, we introduce non-linear temporal registration into the framework in order to normalize for timing differences within the stance phase. We refer to our software framework as STAPP: spatiotemporal analysis of plantar pressure measurements. Using STAPP, we tested our hypothesis on plantar pressure videos from 33 healthy subjects walking at different speeds. Results: As walking speed increased, STAPP was able to identify significant decreases in plantar pressure at mid-stance from the heel through the lateral forefoot. The extent of these plantar pressure decreases have not previously been observed using existing plantar pressure analysis techniques. Significance: We therefore conclude that the subsampling of plantar pressure videos - a task which led to the discarding of gait information in our study - can be avoided using STAPP.}, doi = {10.1016/j.gaitpost.2018.04.029}, author = {Brian G Booth and No{\"e}l L.W. Keijsers and Jan Sijbers and Toon Huysmans} } @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} } @article {1824, title = {White matter microstructural organization of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults}, journal = {European Journal of Neuroscience }, volume = {47}, year = {2018}, pages = {446{\textendash}459}, doi = {10.1111/ejn.13841}, author = {Hamed Zivari Adab and Sima Chalavi and Iseult Beets and Jolien Gooijers and Inge Leunissen and Boris Cheval and Quinten Collier and Jan Sijbers and Ben Jeurissen and S. P. Swinnen and Matthieu Boisgontier} } @proceedings {1904, title = {ACIVS 2017, Advanced Concepts for Intelligent Vision Systems}, volume = {10617}, year = {2017}, author = {J Blanc-Talon and R Penne and Wilfried Philips and D Popescu and Paul Scheunders} } @article {1752, title = {Altered functional brain connectivity in patients with visually induced dizziness}, journal = {NeuroImage: Clinical}, volume = {14}, year = {2017}, pages = {538{\textendash}545}, doi = {http://dx.doi.org/10.1016/j.nicl.2017.02.020}, author = {Angelique Van Ombergen and Lizette Heine and Steven Jillings and Edward Roberts and Ben Jeurissen and V. Van Rompaey and Viviana Mucci and Stefanie Vanhecke and Jan Sijbers and Floris Vanhevel and Stefan Sunaert and Mohamed Ali Bahri and Paul M Parizel and Paul H Van de Heyning and Steven S L Laureys and Floris L Wuyts} } @article {1915, title = {The arcuate fasciculus network and verbal deficits in psychosis}, journal = {Translational Neuroscience}, volume = {8}, year = {2017}, month = {Feb-11-2017}, pages = {117-126}, doi = {10.1515/tnsci-2017-0018}, author = {Kenney, Joanne P.M. and McPhilemy, Genevieve and Scanlon, Cathy and Najt, Pablo and McInerney, Shane and Arndt, Sophia and Scherz, Elisabeth and Byrne, Fintan and Alexander Leemans and Ben Jeurissen and Hallahan, Brian and McDonald, Colm and Cannon, Dara M.} } @article {1789, title = {Can portable tomosynthesis improve the diagnostic value of bedside chest X-ray in the intensive care unit? A proof of concept study}, journal = {European Radiology Experimental}, volume = {1}, year = {2017}, pages = {1-7}, doi = {10.1186/s41747-017-0021-6}, author = {Jeroen Cant and Annemie Snoeckx and Gert Behiels and Paul M Parizel and Jan Sijbers} } @article {1801, title = {Hyperspectral leaf reflectance of Carpines betulus L. saplings for urban air quality estimation}, journal = {Environmental Pollution}, volume = {220}, year = {2017}, pages = {159-167}, author = {Melanka Brackx and Shari Van Wittenberghe and Jolien Verhelst and Paul Scheunders and Roeland Samson} } @mastersthesis {1738, title = {Iterative reconstruction for mobile chest tomosynthesis}, volume = {PhD in Sciences/Physics}, year = {2017}, type = {PhD thesis}, author = {Jeroen Cant} } @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 {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} } @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} } @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} } @article {1723, title = {A safe, cheap and easy-to-use isotropic diffusion phantom for clinical and multicenter studies}, journal = {Medical Physics}, volume = {44}, year = {2017}, pages = {1063{\textendash}1070}, doi = {10.1002/mp.12101}, author = {Pim Pullens and Piet Bladt and Jan Sijbers and Andrew I.R. Maas and Paul M Parizel} } @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 {1805, title = {On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation}, journal = {Environmental Monitoring and Assessment}, volume = {189}, year = {2017}, chapter = {472}, author = {Melanka Brackx and Jolien Verhelst and Paul Scheunders and Roeland Samson} } @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 {1793, title = {An alternative approach for Ī¶-factor measurement using pure element nanoparticles}, journal = {Ultramicroscopy}, volume = {164}, year = {2016}, pages = {11{\textendash}16}, abstract = {It is very challenging to measure the chemical composition of hetero nanostructures in a reliable and quantitative manner. Here, we propose a novel and straightforward approach that can be used to quantify energy dispersive X-ray spectra acquired in a transmission electron microscope. Our method is based on a combination of electron tomography and the so-called Ī¶-factor technique. We will demonstrate the reliability of our approach as well as its applicability by investigating Au-Ag and Au-Pt hetero nanostructures. Given its simplicity, we expect that the method could become a new standard in the field of chemical characterization using electron microscopy.}, keywords = {Bimetallic nanoparticles, EDXS quantification, Electron tomography}, issn = {03043991}, doi = {10.1016/j.ultramic.2016.03.002}, url = {http://linkinghub.elsevier.com/retrieve/pii/S0304399116300134}, author = {Daniele Zanaga and Thomas Altantzis and Jonathan Sanctorum and Bert Freitag and Sara Bals} } @inproceedings {1691, title = {Automatic geometric calibration of chest tomosynthesis using data consistency conditions}, booktitle = {The 4th International Conference on Image Formation in X-Ray Computed Tomography}, year = {2016}, pages = {161-164}, address = {Salt Lake City, Utah, USA}, author = {Jeroen Cant and Gert Behiels and Jan Sijbers} } @inproceedings {1669, title = {Continuous Digital Laminography}, booktitle = {6th Conference on Industrial Computed Tomography}, year = {2016}, address = {Wels, Austria}, url = {http://www.ndt.net/article/ctc2016/papers/ICT2016_paper_id42.pdf}, author = {Jeroen Cant and Gert Behiels and Jan Sijbers} } @article {1715, title = {A distributed ASTRA Toolbox}, journal = {Advanced Structural and Chemical Imaging}, volume = {2}, year = {2016}, doi = {10.1186/s40679-016-0032-z}, author = {Willem Jan Palenstijn and Jeroen B{\'e}dorf and Jan Sijbers and Kees Joost Batenburg} } @article {1600, title = {Easy implementation of advanced tomography algorithms using the ASTRA toolbox with Spot operators}, journal = {Numerical Algorithms}, volume = {71}, number = {3}, year = {2016}, pages = {673-697}, doi = {10.1007/s11075-015-0016-4}, author = {Folkert Bleichrodt and Tristan van Leeuwen and Willem Jan Palenstijn and Wim Van Aarle and Jan Sijbers and Kees Joost Batenburg} } @article {1892, title = {EPR and DFT analysis of biologically relevant chromium(V) complexes with d-glucitol and d-glucose}, journal = {Journal of Inorganic Biochemistry}, volume = {162}, year = {2016}, pages = {216 - 226}, keywords = {1, 2-diolato ligands, DFT, ENDOR, EPR, HYSCORE, Oxidochromium(V)}, issn = {0162-0134}, doi = {https://doi.org/10.1016/j.jinorgbio.2016.07.012}, url = {http://www.sciencedirect.com/science/article/pii/S0162013416302136}, author = {Sabine Van Doorslaer and Quinten Beirinckx and Kevin Nys and Mar{\'\i}a Florencia Mangiameli and Bert Cuypers and Freddy Callens and Henk Vrielinck and Juan Carlos Gonz{\'a}lez} } @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} } @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-MarzaĢn and Sandra Van Aert and Jan Sijbers and Van Tendeloo, Gustaaf and Sara Bals} } @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 {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} } @article {1674, title = {Quantitative 3D analysis of huge nanoparticle assemblies.}, journal = {Nanoscale}, volume = {8}, year = {2016}, month = {2016 Jan 7}, pages = {292-9}, abstract = {Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10,000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.}, issn = {2040-3372}, doi = {10.1039/c5nr06962a}, author = {Daniele Zanaga and Folkert Bleichrodt and Thomas Altantzis and Winckelmans, Naomi and Willem Jan Palenstijn and Jan Sijbers and de Nijs, Bart and Marijn A van Huis and Ana S{\'a}nchez-Iglesias and Luis M Liz-MarzaĢn and van Blaaderen, Alfons and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf} } @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} } @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} } @proceedings {1906, title = {ACIVS 2015, Advanced Concepts for Intelligent Vision Systems}, volume = {9386}, year = {2015}, author = {S Battiato and J Blanc-Talon and G Gallo and Wilfried Philips and D Popescu and Paul Scheunders} } @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} } @inproceedings {1542, title = {Filtered backprojection using algebraic filters; Application to biomedical micro-CT data}, booktitle = {International Symposium on Biomedical Imaging (ISBI)}, year = {2015}, pages = {1596-1599}, author = {Linda Plantagie and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers} } @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} } @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} } @conference {1588, title = {An iterative prior knowledge based reconstruction algorithm for increased temporal/spatial resolution in the CT imaging of fluid flow through solid matter}, year = {2015}, abstract = {The study of fluid flow through solid matter by computed tomography (CT) imaging has a broad range of applications, e.g., in oil production (the manner in which water displaces oil in rocks determines the fraction of oil that can be recovered) and in scientific research on fluid dynamics (validation of fluid flow models) [1-4]. In this work, a novel iterative computed tomography 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 a twofold manner. Firstly, a dynamic reconstruction is generated assuming the existence of stationary regions (the solid matter) and dynamic regions (the fluid flow) throughout the reconstruction domain. This assumption is enforced by sharing iterative updates in the stationary regions over different time frames. Secondly, the fact that a particular voxel in the dynamic region can typically be described by a piecewise constant (PWC) function over time (i.e., the voxel consists of fluid or air) is exploited by estimating a PWC function in a robust manner in all voxels belonging to the dynamic region at intermediate iterations. The proposed reconstruction algorithm was validated on simulation data and on a real neutron tomography dataset (PSI ICON experiment, courtesy of Manchester X-ray Imaging Facility). These experiments demonstrated that the new iterative technique is able to significantly increase the temporal resolution in comparison to more conventional algorithms such as the Simultaneous Iterative Reconstruction Technique (SIRT) or Filtered Backprojection (FBP) [5-6]. [1] V. Cnudde and M. Boone: High-resolution x-ray computed tomography in geosciences: A review of the current technology and applications. Earth-Science Reviews, vol. 123, pp. 1 {\textendash} 17, 2013 [2] S. Akin and A. Kovscek: Computed tomography in petroleum engineering research. Geological Society, London, Special Publications, vol. 215, no. 1, pp. 23{\textendash}38, 2003 [3] O. P. Wennberg, L. Rennan, and R. Basquet: Computed tomography scan imaging of natural open fractures in a porous rock; geometry and fluid flow. Geophysical Prospecting, vol. 57, no. 2, pp. 239{\textendash}249, 2009 [4] M. Kumar, T. J. Senden, A. P. Sheppard, J. P. Middleton, and M. A. Knackstedt: Visualizing and quantifying the residual phase distribution in core material. Petrophysics, vol. 51, no. 5, p. 323, 2010 [5] J. Gregor and T. Benson: Computational analysis and improvement of SIRT. IEEE Trans. Med. Imag., vol. 27, no. 7, pp. 918{\textendash}24, 2008 [6] L. Feldkamp, L. Davis, and J. Kress: Practical cone-beam algorithm. J. Opt. Soc. Am. A, vol. 1, no. 6, pp. 612{\textendash}619, 1984 }, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil 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-MarzaĢn and Sandra Van Aert and Sara Bals and Jan Sijbers and Van Tendeloo, Gustaaf} } @mastersthesis {1631, title = {Model-based iterative reconstruction algorithms for computed tomography}, volume = {PhD in Sciences}, year = {2015}, month = {12/2015}, type = {PhD thesis}, author = {Van Eyndhoven, Geert} } @article {1563, title = {Modeling blurring effects due to continuous gantry rotation: application to region of interest tomography}, journal = {Medical Physics}, volume = {42}, year = {2015}, pages = {2709-2717}, doi = { http://dx.doi.org/10.1118/1.4914422}, author = {Jeroen Cant and Willem Jan Palenstijn and Gert Behiels and Jan Sijbers} } @article {1496, title = {Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials}, journal = {Ultramicroscopy}, volume = {148}, year = {2015}, pages = {10-19}, abstract = {Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm ({\textquotedblleft}POre REconstruction and Segmentation{\textquotedblright}) is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.}, doi = {10.1016/j.ultramic.2014.08.008}, author = {Van Eyndhoven, Geert and Mert Kurttepeli and C. J. {Van Oers} and Pegie Cool and Sara Bals and Kees Joost Batenburg and Jan Sijbers} } @article {1626, title = {Quantitative 3D analysis of huge nanoparticle assemblies}, journal = {Nanoscale}, volume = {8}, year = {2015}, pages = {292-299}, doi = {10.1039/C5NR06962A}, author = {Daniele Zanaga and Folkert Bleichrodt and Thomas Altantzis and Winckelmans, Naomi and Willem Jan Palenstijn and Jan Sijbers and B. van Nijs and Marijn A van Huis and van Blaaderen, Alfons and Ana S{\'a}nchez-Iglesias and Luis M Liz-MarzaĢn and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf} } @inproceedings {1590, title = {Region based 4D tomographic image reconstruction: application to cardiac X-ray CT}, booktitle = {IEEE International Conference on Image Processing}, year = {2015}, pages = {113 - 117}, abstract = {X-ray computed tomography (CT) is a powerful tool for noninvasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting prior knowledge in two ways: the reconstructed object is assumed to consist of both stationary and dynamic regions over time and the dynamic region is assumed to have sparse structures after a proper sparsifying space-time transform. Experiments on simulation data and a real micro CT cardiac mouse dataset show that, with comparable image quality, the radiation dose can be substantially reduced compared to conventional acquisition/reconstruction protocols.}, doi = {10.1109/ICIP.2015.7350770}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers} } @article {forde2015structural, title = {Structural brain network analysis in families multiply affected with bipolar I disorder}, journal = {Psychiatry Research: Neuroimaging}, volume = {234}, number = {1}, year = {2015}, pages = {44{\textendash}51}, publisher = {Elsevier}, author = {Forde, Natalie J and O{\textquoteright}Donoghue, Stefani and Scanlon, Cathy and Louise Emsell and Chaddock, Chris and Alexander Leemans and Ben Jeurissen and Gareth J. Barker and Dara M. Cannon and Murray, Robin M and others} } @mastersthesis {1632, title = {Towards In Loco X-ray Computed Tomography}, year = {2015}, month = {12/2015}, type = {PhD thesis}, author = {Andrei Dabravolski} } @inproceedings {1499, title = {3D imaging of semiconductor components by discrete laminography}, booktitle = {Stress induced phenomena and reliability in 3D microelectronics: AIP Conference Proceedings}, volume = {1601}, year = {2014}, pages = {168-179}, doi = { http://dx.doi.org/10.1063/1.4881350}, author = {Kees Joost Batenburg and Willem Jan Palenstijn and Jan Sijbers} } @conference {1607, title = {Accurate reconstruction of porous samples in CT}, year = {2014}, month = {2014}, abstract = {Quantification of a sample{\textquoteright}s porosity from computed tomography (CT) images is important in many industrial applications. However, in non-standard acquisition set-ups (e.g., limited data or angular range), the reconstruction and subsequent segmentation of pore-space is challenging. In this paper, a novel algorithm exploiting prior knowledge about the porous structure of the scanned is proposed, improving the quality of both reconstruction and segmentation.}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers} } @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} } @mastersthesis {2368, title = {Advances in unmixing of hyperspectral remote sensing imagery}, year = {2014}, type = {PhD thesis}, author = {Dzevdet Burazerovic} } @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} } @article {1421, title = {The anatomy of the clavicle: A Three-dimensional Cadaveric Study}, journal = {Clinical anatomy}, volume = {27}, year = {2014}, month = {2013 Oct 21}, pages = {712{\textendash}723}, abstract = {The clavicle has a complex osteologic structure that makes morphological analysis extremely difficult. A three-dimensional study was conducted to examine the anatomical variations and characteristics of the bone. Sixty-eight human cadaver clavicles were dissected, CAT-scanned, and reconstructed. An automated parameterization and correspondence shape analysis system was developed. A new length, designated as centerline (CL) length, was defined and measured. This length represents the true length of the clavicle. The endpoint length was measured as the distance between two endpoints. The width and curvature were measured in the axial (AX) and frontal (FR) plane and defined along the CL. Next gender and side characteristics and variations were examined. The mean CL length was 159.0 {\textpm} 11.0 mm. The mean endpoint length was 149.4 {\textpm} 10.3 mm, which was statistically significantly shorter than the CL. The male clavicle was significantly longer (166.8 {\textpm} 7.3 mm vs. 151.0 {\textpm} 8.2 mm), wider (14.6 {\textpm} 1.5 mm vs. 12.7 {\textpm} 1.3 mm lateral FR plane, 25.9 {\textpm} 4.1 mm vs. 23.5 {\textpm} 3.0 mm lateral AX plane and 24.7 {\textpm} 2.8 mm vs. 22.8 {\textpm} 2.8 mm medial AX plane), and more curved (10.8 {\textpm} 2.8 mm vs. 8.6 {\textpm} 2.3 mm medial and 10.5 {\textpm} 3.3 mm vs. 9.1 {\textpm} 2.5 mm lateral) than the female one. Left clavicles were significant longer (159.8 {\textpm} 10.9 mm vs. 158.0 {\textpm} 11.2 mm) than right clavicles. A novel three-dimensional system was developed, used and tested in order to explore the anatomical variations and characteristics of the human clavicle. This information, together with the automated system, can be applied to future clavicle populations and to the design of fixation plates for clavicle fractures. Clin. Anat., 2013. {\textcopyright} 2013 Wiley Periodicals, Inc.}, issn = {1098-2353}, doi = {10.1002/ca.22288}, author = {Amit Bernat and Toon Huysmans and Francis Van Glabbeek and Jan Sijbers and Gielen, Jan and Van Tongel, Alexander} } @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} } @article {1678, title = {Filter for Tomographic Reconstructions}, number = {WO2013011031A1}, year = {2014}, chapter = {WO2013011031A1}, author = {Kees Joost Batenburg and Jan Sijbers and Linda Plantagie} } @inproceedings {1543, title = {GPGPU and MIC in accelerated cluster for remote sensed image processing software}, booktitle = {Conference on Big Data from Space (BiDS), 12-14 November, ESRIN, Frascati, Italy}, year = {2014}, author = {Olivier Melet and Toon Huysmans and Michel Hummel and Pierre-Marie Brunet} } @conference {1449, title = {A local enhancement based tomographic reconstruction technique for radiation exposure reduction in cerebral perfusion computed tomography}, year = {2014}, doi = {10.1594/ecr2014/C-0282}, url = {http://posterng.netkey.at/esr/online_viewing/index.php?module=view_postercoverpage\&task=viewcoverpage\&start=0\&ls=authorlist\&pi=121333\&perid=248156\&num=1\&count=1\&cid=515}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg 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 {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 {1436, title = {Region-based iterative reconstruction of structurally changing objects in CT}, journal = {IEEE Transactions on Image Processing}, volume = {23}, year = {2014}, pages = {909-919}, chapter = {909-919}, doi = {10.1109/TIP.2013.2297024}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers} } @conference {1454, title = {Reliable Pore-size Measurements Based on a Procedure Specifically Designed for Electron Tomography Measurements of Nanoporous Samples}, year = {2014}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Cynthia Van Oers and Mert Kurttepeli and Sara Bals and Pegie Cool and Jan Sijbers} } @article {1527, title = {A spectral-unmixing approach to estimate water-mass concentrations in case-II waters}, journal = {IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, volume = {7}, number = {8}, year = {2014}, author = {Dzevdet Burazerovic and Rob Heylen and Dries Raymaekers and Els Knaeps and Paul Scheunders} } @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} } @article {1437, title = {Super-resolution for computed tomography based on discrete tomography}, journal = {IEEE Transactions on Image Processing}, volume = {23}, year = {2014}, pages = {1181 - 1193}, doi = {10.1109/TIP.2013.2297025}, author = {Wim Van Aarle and Kees Joost Batenburg and Gert Van Gompel and Elke Van de Casteele and Jan Sijbers} } @inproceedings {1495, title = {Tomographic image reconstruction from continuous projections}, booktitle = {The third international conference on image formation in X-ray computed tomography}, year = {2014}, month = {06/2014}, pages = {295-298}, address = {Salt Lake City, USA}, author = {Jeroen Cant and Willem Jan Palenstijn and Gert Behiels and Jan Sijbers} } @proceedings {1907, title = {ACIVS 2013, Advanced Concepts for Intelligent Vision Systems}, volume = {8129}, year = {2013}, author = {J Blanc-Talon and A Kazinski and Wilfried Philips and D Popescu and Paul Scheunders} } @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} } @article {1343, title = {Advanced reconstruction algorithms for electron tomography: from comparison to combination}, journal = {Ultramicroscopy}, volume = {127}, year = {2013}, pages = {40{\textendash}47}, author = {Bart Goris and Roelandts, Tom and Kees Joost Batenburg and Hamed Heidari Mezerji and Sara Bals} } @article {1392, title = {Advances in X-ray diffraction contrast tomography: flexibility in the setup geometry and application to multiphase materials}, journal = {Journal of Applied Crystallography}, volume = {46}, year = {2013}, month = {04/2013}, pages = {297 - 311}, issn = {0021-8898}, doi = {10.1107/S0021889813002604}, author = {Reischig, P{\'e}ter and King, Andrew and Nervo, Laura and Vigan{\'o}, Nicola and Guilhem, Yoann and Willem Jan Palenstijn and Kees Joost Batenburg and Preuss, Michael and Ludwig, Wolfgang} } @inproceedings {1399, title = {An Algebraic Reconstruction Technique for the Study of Local Structural Changes during CT}, booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)}, year = {2013}, pages = {137-141}, abstract = {If an object undergoes structural changes during a CT-scan, artefacts are introduced in the reconstruction. Current methods that compensate for these changes assume a continuous deformation model, which is insufficient to capture the complexity of structural changes. In this paper, an iterative method is proposed that incorporates prior knowledge about the changing region in the reconstruction algorithm, which results in significantly more accurate reconstructions.}, author = {Van Eyndhoven, Geert 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} } @inproceedings {1403, title = {The ASTRA Tomography Toolbox}, booktitle = {13th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2013}, volume = {4}, year = {2013}, pages = {1139-1145}, isbn = {978-84-616-2723-3}, author = {Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers} } @article {1407, title = {DART: a new approach for super-resolution reconstruction of license plates}, journal = {Journal of Electronic Imaging}, volume = {22}, year = {2013}, chapter = {041111}, doi = {10.1117/1.JEI.22.4.041111}, url = {http://electronicimaging.spiedigitallibrary.org/article.aspx?articleid=1733763}, author = {Karim Zarei Zefreh and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers} } @article {1409, title = {Detecting the adjacency effect in hyperspectral imagery with spectral unmixing techniques}, journal = {IEEE JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, volume = {6}, year = {2013}, pages = {1070-1078}, author = {Dzevdet Burazerovic and Bert Geens and Rob Heylen and S Sterckx and Paul Scheunders} } @conference {1405, title = {Discrete Tomography in MRI: a proof of concept}, volume = {21}, year = {2013}, pages = {2662}, author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers} } @article {1404, title = {Discrete Tomography in MRI: a Simulation Study}, journal = {Fundamenta Informaticae}, volume = {125}, year = {2013}, pages = {223-237}, doi = {10.3233/FI-2013-861}, author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers} } @article {1370, title = {Dynamic angle selection in binary tomography}, journal = {Computer Vision and Image Understanding}, volume = {117}, year = {2013}, pages = {306{\textendash}318}, doi = {http://dx.doi.org/10.1016/j.cviu.2012.07.005}, author = {Kees Joost Batenburg and Willem Jan Palenstijn and Peter Balazs and Jan Sijbers} } @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 {1677, title = {Dynamic tomography angle selection}, number = {PCT/EP2012/071421}, year = {2013}, chapter = {WO2013064472 A1}, issn = {US2014307934A1}, author = {Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1423, title = {Fast Tomographic Reconstruction from Highly Limited Data Using Artificial Neural Networks}, booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)}, year = {2013}, pages = {109-112}, author = {Daan Pelt and Jan Sijbers and Kees Joost Batenburg} } @article {1410, title = {Hyperspectral remote sensing data analysis and future challenges}, journal = {IEEE Geoscience and Remote Sensing Magazine}, volume = {1}, year = {2013}, pages = {6-36}, author = {Jose Bioucas-Dias and Antonio Plaza and Gustavo Camps-Valls and Paul Scheunders and Nasser Nasrabadi and Jocedlyn Chanussot} } @article {1368, title = {Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study}, journal = {Biologicial Psychiatry}, volume = {73}, year = {2013}, pages = {194-201}, doi = {http://dx.doi.org/10.1016/j.biopsych.2012.09.023}, author = {Louise Emsell and Alexander Leemans and Camilla Langan and Wim Van Hecke and Gareth J. Barker and Peter McCarthy and Ben Jeurissen and Jan Sijbers and Stefan Sunaert and Dara M. Cannon and Colm McDonald} } @mastersthesis {1428, title = {Local Prior Knowledge in Tomography}, volume = {PhD in Sciences: Physics}, year = {2013}, month = {11/2013}, type = {PhD thesis}, author = {Roelandts, Tom} } @inproceedings {1400, title = {Localizing DART using the Reconstructed Residual Error}, booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)}, volume = {Book of Abstracts: Talks}, year = {2013}, pages = {113-116}, address = {Ghent, Belgium}, author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1422, title = {Practical Error Bounds for Binary Tomography}, booktitle = {1st International Conference on Tomography of Materials and Structures}, year = {2013}, pages = {97-100}, author = {Wagner Fortes and Jan Sijbers and Kees Joost Batenburg} } @conference {1398, title = {Region-Based SIRT algorithm for the reconstrcution of phase bins in dynamic micro-CT}, year = {2013}, author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers} } @article {1431, title = {Statistical shape modeling and population analysis of the aortic root of TAVI patients}, journal = {Journal of Medical Devices}, volume = {7}, year = {2013}, month = {12/2013}, publisher = {ASME}, edition = {040925 }, abstract = {The new transcatheter technique to implant synthetic aortic valves offers a treatment to patients previously considered untreatable. However the majority of patients suffer from leakage alongside the implant. Using a statistical shape model of the anatomy a correlation was discovered between leakage and the shape of the sinuses of valsalva.}, doi = {10.1115/1.4025904}, url = {http://medicaldevices.asmedigitalcollection.asme.org/article.aspx?articleid=1767192}, author = {Bosmans, Bart and Toon Huysmans and Wirix-Speetjens, Roel and Verschueren, Peter and Jan Sijbers and Bosmans, Johan and Vander Sloten, Jos} } @article {1328, title = {Super-Resolution for Multislice Diffusion Tensor Imaging}, journal = {Magnetic Resonance in Medicine}, volume = {69}, year = {2013}, pages = {103{\textendash}113}, abstract = {Diffusion weighted (DW) magnetic resonance images are often recorded with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise and acquisition time, images are generally acquired with either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing and visualization. In this paper, we propose a super-resolution method for diffusion weighted imaging that combines anisotropic multislice images to enhance the spatial resolution of diffusion tensor (DT) data. Each DW image is reconstructed from a set of arbitrarily oriented images with a low through-plane resolution. The quality of the reconstructed DW images was evaluated by DT metrics and tractography. Experiments with simulated data, a hardware DTI phantom, as well as in vivo human brain data were conducted. Our results show a significant increase in spatial resolution of the DT data while preserving high signal to noise ratio.}, doi = {10.1002/mrm.24233}, author = {Dirk H J Poot and Ben Jeurissen and Yannick Bastiaensen and Jelle Veraart and Wim Van Hecke and Paul M Parizel and Jan Sijbers} } @article {1419, title = {Super-Resolution of License Plate Images using Algebraic Reconstruction Technique}, journal = {Journal of Image and Graphics}, volume = {1}, year = {2013}, month = {2013}, pages = {94 - 98}, publisher = {Engineering and Technology Publishing (ETP)}, address = {USA}, abstract = {In this paper, an iterative super-resolution reconstruction method is introduced for license plate recognition. A high-resolution image of the license plate is reconstructed by fusing the information derived from a set of subpixel shifted low-resolution images. The reconstruction problem is formulated as a system of linear equations that is solved by using the simultaneous algebraic reconstruction technique (SIRT). Simulation experiments show that SIRT can reconstruct a HR image with superior quality compared to conventional super-resolution reconstruction methods.}, keywords = {algebraic reconstruction technique, license plate, reconstruction, SIRT, super-resolution}, issn = {23013699}, doi = {10.12720/joig.1.2.94-98}, url = {http://www.joig.org/index.php?m=content\&c=index\&a=show\&catid=31\&id=41}, author = {Karim Zarei Zefreh and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers} } @article {1320, title = {Accurate segmentation of dense nanoparticles by partially discrete electron tomography}, journal = {Ultramicroscopy}, volume = {114}, year = {2012}, pages = {96-105}, author = {Roelandts, Tom and Kees Joost Batenburg and E. Biermans and C. Kubel and Sara Bals and Jan Sijbers} } @proceedings {1373, title = {ACIVS 2012, Advanced Concepts for Intelligent Vision Systems}, volume = {7517}, year = {2012}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu and Paul Scheunders and P. Zemcik} } @article {1350, title = {Automatic parameter estimation for the Discrete Algebraic Reconstruction Technique (DART)}, journal = {IEEE Transactions on Image Processing}, volume = {21}, year = {2012}, pages = {4608-4621}, doi = {10.1109/TIP.2012.2206042}, author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1367, title = {Combined Motion Estimation and Reconstruction in Tomography}, booktitle = {12th European Conference on Computer Vision}, volume = {7583}, year = {2012}, pages = {12-21}, publisher = {Lecture Notes on Computer Science}, organization = {Lecture Notes on Computer Science}, address = {Firenze, Italy}, abstract = {If objects or patients move during a CT scan, reconstructions suffer from severe motion artifacts. Time dependent computed tomography (4DCT) tries to minimize these artifacts by estimating motion and/or reconstruction simultaneously. Most current methods assume a known deformation or a reconstruction without artifacts at a certain time point. This work explores the possibilities of estimating the motion model and reconstruction simultaneously. It does so by modifying the simultaneous iterative reconstruction technique (SIRT) to incorporate motion (trans-SIRT) and uses this method in an optimization routine that computes motion and reconstruction at the same time. Results show that the optimization routine is able to estimate motion accurately, assuming only the type of parametrization for the motion model. Our approach can potentially be extended to more complex motion models.}, doi = {10.1007/978-3-642-33863-2_2}, author = {Van Eyndhoven, Geert and Jan Sijbers and Kees Joost Batenburg} } @article {CampI.L.N.mverhoyejveraartwvheckeE.S.jsijbersA.avdlinde2011, title = {A complementary DTI-histological study in a model of Huntingtons disease}, journal = {Neurobiology of Aging}, volume = {33}, number = {5}, year = {2012}, pages = {945-959}, doi = {http://dx.doi.org/10.1016/j.neurobiolaging.2010.07.001}, author = {N. Van Camp and Ines Blockx and L. Camon and N. de Vera and Marleen Verhoye and Jelle Veraart and Wim Van Hecke and E. Martinez and Guadelupe S. and Jan Sijbers and A. Planas and Annemie Van Der Linden} } @article {1515, title = {Extraction of airways from CT (EXACT{\textquoteright}09).}, journal = {IEEE Transactions on Medical Imaging}, volume = {31}, year = {2012}, month = {2012 Nov}, pages = {2093-107}, abstract = {This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74\% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.}, keywords = {Algorithms, Analysis of Variance, Databases, Factual, Humans, Lung, Radiographic Image Enhancement, Tomography, X-Ray Computed, Trachea}, issn = {1558-254X}, doi = {10.1109/TMI.2012.2209674}, author = {Lo, Pechin and van Ginneken, Bram and Reinhardt, Joseph M and Yavarna, Tarunashree and de Jong, Pim A and Irving, Benjamin and Fetita, Catalin and Ortner, Margarete and R{\^o}mulo Pinho and Jan Sijbers and Feuerstein, Marco and Fabija{\'n}ska, Anna and Bauer, Christian and Beichel, Reinhard and Mendoza, Carlos S and Wiemker, Rafael and Lee, Jaesung and Reeves, Anthony P and Born, Silvia and Weinheimer, Oliver and van Rikxoort, Eva M and Tschirren, Juerg and Mori, Ken and Odry, Benjamin and Naidich, David P and Hartmann, Ieneke and Eric A. Hoffman and Prokop, Mathias and Pedersen, Jesper H and de Bruijne, Marleen} } @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} } @proceedings {1463, title = {Hyperspectral Image Compression Using 3d Discrete Cosine Transform and Support Vector Machine Learning}, year = {2012}, address = {Montreal, Canada}, author = {Azam Karami and S. Beheshti and M.Yazdi} } @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} } @article {1516, title = {Improved sensitivity to cerebral white matter abnormalities in Alzheimer{\textquoteright}s disease with spherical deconvolution based tractography.}, journal = {PloS one}, volume = {7}, year = {2012}, month = {2012}, pages = {e44074}, abstract = {Diffusion tensor imaging (DTI) based fiber tractography (FT) is the most popular approach for investigating white matter tracts in vivo, despite its inability to reconstruct fiber pathways in regions with "crossing fibers." Recently, constrained spherical deconvolution (CSD) has been developed to mitigate the adverse effects of "crossing fibers" on DTI based FT. Notwithstanding the methodological benefit, the clinical relevance of CSD based FT for the assessment of white matter abnormalities remains unclear. In this work, we evaluated the applicability of a hybrid framework, in which CSD based FT is combined with conventional DTI metrics to assess white matter abnormalities in 25 patients with early Alzheimer{\textquoteright}s disease. Both CSD and DTI based FT were used to reconstruct two white matter tracts: one with regions of "crossing fibers," i.e., the superior longitudinal fasciculus (SLF) and one which contains only one fiber orientation, i.e. the midsagittal section of the corpus callosum (CC). The DTI metrics, fractional anisotropy (FA) and mean diffusivity (MD), obtained from these tracts were related to memory function. Our results show that in the tract with "crossing fibers" the relation between FA/MD and memory was stronger with CSD than with DTI based FT. By contrast, in the fiber bundle where one fiber population predominates, the relation between FA/MD and memory was comparable between both tractography methods. Importantly, these associations were most pronounced after adjustment for the planar diffusion coefficient, a measure reflecting the degree of fiber organization complexity. These findings indicate that compared to conventionally applied DTI based FT, CSD based FT combined with DTI metrics can increase the sensitivity to detect functionally significant white matter abnormalities in tracts with complex white matter architecture.}, keywords = {Aged, 80 and over, Alzheimer Disease, Cerebrum, Cognition, Corpus Callosum, diffusion tensor imaging, Female, Humans, Male, Memory, Nerve Fibers, Myelinated}, issn = {1932-6203}, doi = {10.1371/journal.pone.0044074}, author = {Reijmer, Yael D and Alexander Leemans and Heringa, Sophie M and Wielaard, Ilse and Ben Jeurissen and Koek, Huiberdina L and Biessels, Geert Jan} } @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} } @conference {1430, title = {Segmentation of MR Images by k-space distance minimization: a proof of concept}, volume = {25}, year = {2012}, pages = {63-64}, author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1360, title = {Spatial Variations in Reconstruction Methods for CT}, booktitle = {The Second International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting)}, year = {2012}, month = {07/2012}, pages = {170-173}, author = {Linda Plantagie and Willem Jan Palenstijn and Jan Sijbers and Kees Joost Batenburg} } @mastersthesis {1327, title = {Tomographic segmentation and discrete tomography for quantitative analysis of transmission tomography data}, year = {2012}, pages = {190}, school = {University of Antwerp}, type = {PhD thesis}, address = {Antwerp, Belgium}, author = {Wim Van Aarle} } @inproceedings {1353, title = {Unmixing for detection and quantification of adjacency effects}, booktitle = {IEEE IGARSS2012, International Geoscience and Remote Sensing Symposium, Munich, July 22-27}, year = {2012}, pages = {3090-3093}, author = {Dzevdet Burazerovic and Bert Geens and Rob Heylen and S Sterckx and Paul Scheunders} } @inproceedings {1358, title = {Visualizing the Segmentation Error of a Tomogram using the Residual Projection Error}, booktitle = {The Second International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting)}, year = {2012}, pages = {293-296}, address = {Salt Lake City, UT, USA}, author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers} } @proceedings {1235, title = {ACIVS 2011, Advanced Concepts for Intelligent Vision Systems}, volume = {6915}, year = {2011}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu and R. Kleihorst and Paul Scheunders} } @article {zmaiR.jbatenbumverhoyepscheundjsijbers2011, title = {Bias field reduction by localized Lloyd-Max quantization}, journal = {Magnetic Resonance Imaging}, volume = {29}, year = {2011}, pages = {536-545}, doi = {http://dx.doi.org/10.1016/j.mri.2010.10.015}, author = {Zhenhua Mai and Rudolf Hanel and Kees Joost Batenburg and Marleen Verhoye and Paul Scheunders and Jan Sijbers} } @inproceedings {1298, title = {Bone segmentation using discrete tomography}, booktitle = {Micro-CT User Meeting}, year = {2011}, pages = {178-183}, isbn = {9789081678100}, issn = {2033-8031}, author = {Elke Van de Casteele and Kees Joost Batenburg and Salmon, Phil and Jan Sijbers} } @conference {1551, title = {Constrained spherical deconvolution based tractography and cognition in Alzheimer{\textquoteright}s disease}, year = {2011}, address = {Qu{\'e}bec, Canada}, author = {Reijmer, Yael D and Alexander Leemans and Heringa, Sophie M and Wielaard, Ilse and Ben Jeurissen and Koek, Huiberdina L and Biessels, Geert Jan} } @conference {1552, title = {Constrained spherical deconvolution based tractography and cognition in Alzheimer{\textquoteright}s disease}, year = {2011}, address = {Paris, France}, author = {Reijmer, Yael D and Alexander Leemans and Heringa, Sophie M and Wielaard, Ilse and Ben Jeurissen and Koek, Huiberdina L and Biessels, Geert Jan} } @conference {1549, title = {Constrained spherical deconvolution based tractography and cognition in Alzheimer{\textquoteright}s disease}, volume = {5}, year = {2011}, address = {Lille, France}, author = {Reijmer, Yael D and Alexander Leemans and Heringa, Sophie M and Wielaard, Ilse and Ben Jeurissen and Koek, Huiberdina L and Biessels, Geert Jan} } @article {jbatenbujsijbers2011, title = {DART: A practical reconstruction algorithm for discrete tomography}, journal = {IEEE Transactions on Image Processing}, volume = {20}, number = {9}, year = {2011}, pages = {2542-2553}, doi = {10.1109/TIP.2011.2131661}, author = {Kees Joost Batenburg and Jan Sijbers} } @conference {1550, title = {Diffusion tensor imaging and cognition in Alzheimer{\textquoteright}s disease: the influence of crossing fibers}, year = {2011}, address = {Lunteren, The Netherlands}, author = {Wielaard, Ilse and Reijmer, Yael D and Alexander Leemans and Heringa, Sophie M and Ben Jeurissen and Koek, Huiberdina L and Biessels, Geert Jan} } @inproceedings {1429, title = {Efficient parameter estimation for discrete tomography using adaptive modeling}, booktitle = {11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine}, year = {2011}, month = {07/2011}, author = {Wim Van Aarle and K. Crombecq and I. Couckuyt and Kees Joost Batenburg and Jan Sijbers} } @article {HeylenBurazerovicpscheund2011, title = {Fully constrained least-squares spectral unmixing by simplex projection}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {49}, year = {2011}, pages = {4112-4122}, author = {Rob Heylen and Dzevdet Burazerovic and Paul Scheunders} } @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} } @conference {1303, title = {Mediolateral shape and curvature analysis of the clavicle}, year = {2011}, month = {June}, author = {Van Tongel, Alexander and Toon Huysmans and Amit Bernat and Jan Sijbers and Francis Van Glabbeek} } @article {jveraartdpootwvheckeBlockxavdlindemverhoyejsijbers2011, title = {More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging}, journal = {Magnetic Resonance in Medicine}, volume = {65}, number = {1}, year = {2011}, month = {January}, pages = {138-145}, doi = {10.1002/mrm.22603}, author = {Jelle Veraart and Dirk H J Poot and Wim Van Hecke and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers} } @article {HeylenBurazerovicpscheund2011, title = {Nonlinear spectral unmixing by geodesic simplex volume maximization}, journal = {IEEE Journal of Selected Topics in Signal Processing}, volume = {5}, number = {3}, year = {2011}, pages = {534-542}, author = {Rob Heylen and Dzevdet Burazerovic and Paul Scheunders} } @article {wvaarlejbatenbujsijbers2011, title = {Optimal threshold selection for segmentation of dense homogeneous objects in tomographic reconstructions}, journal = {IEEE Transactions on Medical Imaging}, volume = {30}, number = {4}, year = {2011}, pages = {980-989}, doi = {http://dx.doi.org/doi:10.1109/TMI.2010.2104328}, author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1194, title = {PDART: A Partially Discrete Algorithm for the Reconstruction of Dense Particles}, booktitle = {11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D)}, year = {2011}, pages = {448-451}, address = {Potsdam, Germany}, author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers} } @article {1249, title = {Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)}, journal = {Journal of structural biology}, volume = {176}, year = {2011}, month = {2011 Nov}, pages = {250-253}, abstract = {Iterative reconstruction algorithms are becoming increasingly important in electron tomography of biological samples. These algorithms, however, impose major computational demands. Parallelization must be employed to maintain acceptable running times. Graphics Processing Units (GPUs) have been demonstrated to be highly cost-effective for carrying out these computations with a high degree of parallelism. In a recent paper by Xu et al. (2010), a GPU implementation strategy was presented that obtains a speedup of an order of magnitude over a previously proposed GPU-based electron tomography implementation. In this technical note, we demonstrate that by making alternative design decisions in the GPU implementation, an additional speedup can be obtained, again of an order of magnitude. By carefully considering memory access locality when dividing the workload among blocks of threads, the GPU{\textquoteright}s cache is used more efficiently, making more effective use of the available memory bandwidth.}, issn = {1095-8657}, doi = {10.1016/j.jsb.2011.07.017}, author = {Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers} } @article {jveraartB.T.wvheckeI.bjeurissY.avdlindeA.mverhoyejsijbers2011, title = {Population-averaged diffusion tensor imaging atlas of the Sprague Dawley rat brain}, journal = {NeuroImage}, volume = {58}, year = {2011}, pages = {975-983}, doi = {10.1016/j.neuroimage.2011.06.063}, author = {Jelle Veraart and Trygve B Leergaard and Antonsen, Bj{\o}rnar T and Wim Van Hecke and Ines Blockx and Ben Jeurissen and Yi Jiang and Annemie Van Der Linden and Allan G Johnson and Marleen Verhoye and Jan Sijbers} } @article {jbatenbuwvaarlejsijbers2011, title = {A Semi-Automatic Algorithm for Grey Level Estimation in Tomography}, journal = {Pattern Recognition Letters}, volume = {32}, number = {9}, year = {2011}, month = {July}, pages = {1395-1405}, author = {Kees Joost Batenburg and Wim Van Aarle and Jan Sijbers} } @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} } @inproceedings {BurazerovicHeylenpscheund2011, title = {Towards streaming hyperspectral endmember extraction}, booktitle = {IEEE IGARSS2011, IEEE International Geoscience and Remote Sensing Symposium , Vancouver, July 25-29}, year = {2011}, author = {Dzevdet Burazerovic and Rob Heylen and Paul Scheunders} } @conference {1204, title = {Ultra-High Resolution Electron Tomography for Materials Science: A Roadmap}, year = {2011}, address = {Nashville, TN, United States}, doi = {http://dx.doi.org/10.1017/S143192761100554X}, author = {Kees Joost Batenburg and Sara Bals and Sandra Van Aert and Roelandts, Tom and Jan Sijbers} } @inproceedings {wvaarlegvgompeljbatenbuevdcastejsijbers2010, title = {A 3-dimensional discrete tomography approach for superresolution micro-CT images: application to foams}, booktitle = {The first international conference on image formation in X-ray computed tomography}, year = {2010}, month = {June}, pages = {45-48}, author = {Wim Van Aarle and Gert Van Gompel and Kees Joost Batenburg and Elke Van de Casteele and Jan Sijbers}, editor = {Fr{\'e}d{\'e}ric Noo} } @proceedings {1236, title = {ACIVS 2010, Advanced Concepts for Intelligent Vision Systems}, volume = {6474 \& 6475}, year = {2010}, publisher = {Springer}, author = {J Blanc-Talon and D. Bone and Wilfried Philips and D Popescu and Paul Scheunders} } @conference {jveraartAntonsenBlockxwvheckeJiangJohnsonavdlindeLeergaardmverhoyejsijbers2010, title = {Construction of a population based diffusion tensor image atlas of the Sprague Dawley rat brain}, year = {2010}, month = {May}, address = {Stockholm, Sweden}, author = {Jelle Veraart and Antonsen, Bj{\o}rnar T and Ines Blockx and Wim Van Hecke and Yi Jiang and Allan G Johnson and Annemie Van Der Linden and Trygve B Leergaard and Marleen Verhoye and Jan Sijbers} } @article {jbatenbujsijbersH.F.E.2010, title = {DART: A Robust Algorithm for Fast Reconstruction of 3D Grain Maps}, journal = {Journal of Applied Crystallography}, volume = {43}, year = {2010}, pages = {1464-1473}, doi = {https://doi.org/10.1107/S0021889810034114}, author = {Kees Joost Batenburg and Jan Sijbers and H.F. Poulsen and E. Knudsen} } @inproceedings {gvgompeljbatenbuevdcastewvaarlejsijbers2010, title = {A discrete tomography approach for superresolution micro-CT images}, booktitle = {IEEE International Symposium on Biomedical Imaging}, year = {2010}, month = {April}, pages = {816-819}, address = {Rotterdam}, author = {Gert Van Gompel and Kees Joost Batenburg and Elke Van de Casteele and Wim Van Aarle and Jan Sijbers} } @inproceedings {HeylenBurazerovicScheunders2010, title = {A graph-based method for non-linear unmixing of hyperspectral imagery}, booktitle = {IEEE IGARSS2010, IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Haway, July 25-30}, year = {2010}, pages = {197-200}, author = {Rob Heylen and Dzevdet Burazerovic and Paul Scheunders} } @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} } @conference {jveraartwvheckedpootBlockxavdlindemverhoyejsijbers2010, title = {A more accurate and b-value independent estimation of diffusion parameters using Diffusion Kurtosis Imaging}, year = {2010}, month = {January}, pages = {10}, address = {Utrecht, the Netherlands}, author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers} } @conference {jveraartwvheckedpootBlockxavdlindemverhoyejsijbers2010, title = {A more accurate and b-value independent estimation of diffusion parameters using Diffusion Kurtosis Imaging,}, year = {2010}, month = {May}, address = {Stockholm, Sweden}, author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers} } @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 {jveraartwvheckeBlockxavdlindemverhoyejsijbers2010, title = {Non-Rigid coregistration of diffusion kurtosis data}, booktitle = {Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on}, year = {2010}, month = {April}, pages = {392-395}, address = {Rotterdam, the Netherlands}, author = {Jelle Veraart and Wim Van Hecke and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers} } @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} } @conference {1203, title = {Partially Discrete Tomography for the Reconstruction of Dense Particles}, year = {2010}, pages = {I7.19}, address = {Rio de Janeiro, Brazil}, author = {Roelandts, Tom and Kees Joost Batenburg and E. Biermans and Sara Bals and Jan Sijbers} } @inproceedings {1568, title = {Projection and backprojection in tomography: design choices and considerations}, booktitle = {Workshop on Applications of Discrete Geometry and Mathematical Morphology}, year = {2010}, pages = {106-110}, author = {Kees Joost Batenburg and Willem Jan Palenstijn and Jan Sijbers} } @article {jbatenbuBalsjsijbersKubelMidgleyHernandezKaiserEncinaCoronadoTendeloo2009, title = {3D imaging of nanomaterials by discrete tomography}, journal = {Ultramicroscopy}, volume = {109}, year = {2009}, pages = {730-740}, doi = {10.1016/j.ultramic.2009.01.009}, author = {Kees Joost Batenburg and Sara Bals and Jan Sijbers and C. Kubel and P.A. Midgley and J.C. Hernandez and U. Kaiser and E.R. Encina and E.A. Coronado and Van Tendeloo, Gustaaf} } @proceedings {1237, title = {ACIVS 2009, Advanced Concepts for Intelligent Vision Systems}, volume = {5807}, year = {2009}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu and Paul Scheunders} } @article {jbatenbujsijbers2009, title = {Adaptive thresholding of tomograms by projection distance minimization}, journal = {Pattern Recognition}, volume = {42}, number = {10}, year = {2009}, month = {April}, pages = {2297-2305}, doi = {10.1016/j.patcog.2008.11.027}, author = {Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1417, title = {Development of a Machine Vision System to Monitor a Grinding Mill Prototype}, booktitle = {12th European Symposium on Comminution and Classification (ESCC 2009)}, year = {2009}, author = {Timo Roine and Pietil{\"a}, Janne and Kaartinen, Jani and Blanz, Peter and Rantala, Pertti} } @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} } @article {1375, title = {Diffusion tensor imaging in a rat model of Parkinson{\textquoteright}s disease after lesioning of the nigrostriatal tract.}, journal = {NMR in biomedicine}, volume = {22}, year = {2009}, month = {2009 Aug}, pages = {697-706}, abstract = {Parkinson{\textquoteright}s disease (PD) is characterised by degeneration of the nigrostrial connection causing dramatic changes in the dopaminergic pathway underlying clinical pathology. Till now, no MRI tools were available to follow up any specific PD-related neurodegeneration. However, recently, diffusion tensor imaging (DTI) has received considerable attention as a new and potential in vivo diagnostic tool for various neurodegenerative diseases. To assess this in PD, we performed DTI in the acute 6-hydroxydopamine (6-OHDA) rat model of PD to evaluate diffusion properties in the degenerating nigrostriatal pathway and its connecting structures. Injection of a neurotoxin in the striatum causes retrograde neurodegeneration of the nigrostriatal tract, and selective degeneration of nigral neurons. The advantage of this model is that the lesion size is well controllable by the injected dose of the toxin. The degree of functional impairment was evaluated in vivo using the amphetamine rotation test and microPET imaging of the dopamine transporter (DAT). Despite a nearly complete lesion of the nigrostriatal tract, DTI changes were limited to the ipsilateral substantia nigra (SN). In this study we demonstrate, using voxel-based statistics (VBS), an increase in fractional anisotropy (FA), whereas all eigenvalues were significantly decreased. VBS enabled us to visualise neurodegeneration of a cluster of neurons but failed to detect degeneration of more diffuse microstructures such as the nigrostriatal fibres or the dopaminergic endings in the striatum. VBS without a priori information proved to be better than manual segmentation of brain structures as it does not suffer from volume averaging and is not susceptible to erroneous segmentations of brain regions that show very little contrast on MRI images such as SN.}, keywords = {Animals, Behavior, Animal, Diffusion Magnetic Resonance Imaging, Disease Models, Animal, Female, Imaging, Three-Dimensional, Immunohistochemistry, Parkinson Disease, Positron-Emission Tomography, Rats, Rats, Wistar, Substantia Nigra}, issn = {1099-1492}, doi = {10.1002/nbm.1381}, author = {N. Van Camp and Ines Blockx and Marleen Verhoye and Casteels, Cindy and Coun, Frea and Alexander Leemans and Jan Sijbers and Veerle Baekelandt and Koen Van Laere and Annemie Van Der Linden} } @inproceedings {svdmaarjbatenbujsijbers2009, title = {Experiences with Cell-BE and GPU for tomography}, booktitle = {Embedded COmputer Systems: Architectures, Modeling, and Simulation - 9th International Workshop, SAMOS 2009 - Proceedings}, year = {2009}, month = {July}, pages = {298-307}, publisher = {Springer-Verlag Berlin Heidelberg}, organization = {Springer-Verlag Berlin Heidelberg}, author = {S. van der Maar and Kees Joost Batenburg and Jan Sijbers}, editor = {Koen Bertels and Stephan Wong} } @conference {BernatthuysmanGlabbeekjsijbersrpinhoGielen2009, title = {Exploring the Clavicle: Morphometric Differences Using a 3D Model}, year = {2009}, month = {February}, address = {Las Vegas,Nevada}, author = {Amit Bernat and Toon Huysmans and Francis Van Glabbeek and Jan Sijbers and R{\^o}mulo Pinho and Jan L Gielen} } @article {jbatenbujsijbers2009, title = {Generic iterative subset algorithms for discrete tomography}, journal = {Discrete Applied Mathematics}, volume = {157}, number = {3}, year = {2009}, pages = {438-451}, doi = {https://doi.org/10.1016/j.dam.2008.05.033}, author = {Kees Joost Batenburg and Jan Sijbers} } @inproceedings {jbatenbuwvaarlejsijbers2009, title = {Grey Level Estimation for Discrete Tomography}, booktitle = {Discrete Geometry for Computer Imaging}, series = {Lecture Notes in Computer Science}, volume = {5810}, year = {2009}, month = {September}, pages = {517-529}, publisher = {Springer}, organization = {Springer}, doi = {https://doi.org/10.1007/978-3-642-04397-0_44}, author = {Kees Joost Batenburg and Wim Van Aarle and Jan Sijbers}, editor = {Srecko Brlek} } @conference {jveraartBlockxwvheckemverhoyeavdlindejsijbers2009, title = {Improved non rigid coregistration of diffusion kurtosis images by incorporating diffusion kurtosis tensor information}, year = {2009}, month = {October}, pages = {36}, address = {Antalya, Turkey}, author = {Jelle Veraart and Ines Blockx and Wim Van Hecke and Marleen Verhoye and Annemie Van Der Linden and Jan Sijbers} } @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 {jbatenbujsijbers2009, title = {Optimal Threshold Selection for Tomogram Segmentation by Projection Distance Minimization}, journal = {IEEE Transactions on Medical Imaging}, volume = {28}, number = {5}, year = {2009}, month = {June}, pages = {676-686}, doi = {10.1109/TMI.2008.2010437}, author = {Kees Joost Batenburg and Jan Sijbers} } @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} } @article {1614, title = {Osteologic exploration of the clavicle: a new approach}, journal = {The FASEB Journal}, volume = {23}, year = {2009}, edition = { (1_MeetingAbstracts)}, chapter = {LB9}, abstract = {Introduction Clavicles have a complex osteologic structure which makes a morphometric analysis extremely difficult. Our analysis shows the exact measurements and variations of the clavicle. Materials and Methods 90 clavicles were dissected, CAT scanned and reconstructed. All measurements were automatically performed. The length and curvatures were calculated around the central line and for each cross-section the average, sagittal and axial diameter was calculated. Results The average length is 163{\textpm}11 mm. For the length, there is a 9\% difference between the gender and 1.2\% between the left and right clavicle. Between the genders there is a volume difference of 36\%. The extremities show the biggest diameter, this decrease as approaching to the inflexion point, which is the smallest average diameter. In the axial view the acromial curvature is shorter and more curved than the sternal one. In males, the maximum acromial curvature has a difference of 18\% and the maximum sternal curvature a difference of 4\% compared with the females. In the coronal view there is a concave curvature with a maximum of 6 mm. In females the acromial end bends more posteroinferiorly. Discussion This is the first 3D analysis performed on the clavicle. Females have a smaller clavicle with a shorter and less curved acromial curvature and a posteroinferior bending. The right clavicle is slightly shorter, thicker and more robust.}, author = {Hilde Elisa Bortier and Amit Bernat and Toon Huysmans and Francis Van Glabbeek and Jan Sijbers and R{\^o}mulo Pinho and Gielen, Jan and Guy Hubens} } @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 {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.} } @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} } @proceedings {1238, title = {ACIVS 2008, Advanced Concepts for Intelligent Vision Systems}, volume = {5259}, year = {2008}, author = {J Blanc-Talon and S. Bourenanne and Wilfried Philips and D Popescu and Paul Scheunders} } @inproceedings {svdmaarjbatenbujsijbers2008, title = {Algebraic tomographic reconstruction on the GPU}, booktitle = {Li{\`e}ge Image Days 2008: Medical Imaging}, year = {2008}, month = {March}, author = {S. van der Maar and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {jbatenbujsijbers2008, title = {Automatic local thresholding of tomographic reconstructions based on the projection data}, booktitle = {SPIE Medical Imaging}, volume = {6913}, year = {2008}, month = {February}, pages = {69132}, address = {San Diego, CA, USA}, author = {Kees Joost Batenburg and Jan Sijbers}, editor = {Jiang Hsieh, Ehsan Samei} } @conference {1493, title = {Computed tomography on all scales using the ASTRA toolbox}, year = {2008}, author = {Wim Van Aarle and S. van der Maar and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {1295, title = {Evaluation of conservation treatments for archeological waterlogged wooden artifacts}, booktitle = {9th International Conference on NDT of Art}, year = {2008}, author = {Bugani, Simone and Cloetens, Peter and Colombini, Maria Perla and Giachi, Gianna and Janssens, Koen and Modugno, Francesca and Morselli, Luciano and Elke Van de Casteele} } @inproceedings {Haneljbatenbujsijbers2008, title = {Fast bias field estimation by localized Lloyd-Max quantization}, booktitle = {SPIE Medical Imaging}, year = {2008}, month = {February}, address = {San Diego, CA, USA}, author = {Rudolf Hanel and Kees Joost Batenburg and Jan Sijbers} } @conference {1382, title = {FASTRA: Fast Tomographic Reconstructions Using an Eight GPU Desktop Super Computer}, year = {2008}, address = {San Jose, California, USA}, author = {S. van der Maar and Kees Joost Batenburg and Toon Huysmans and Jan Sijbers} } @conference {thuysmanBernatrpinhojsijbersGlabbeeckParizelBortier2008, title = {A Framework for Morphometric Analysis of Long Bones: Application to the Human Clavicle}, year = {2008}, month = {March}, author = {Toon Huysmans and Amit Bernat and R{\^o}mulo Pinho and Jan Sijbers and Francis Van Glabbeek and Paul M Parizel and H. Bortier} } @article {BoumansVignalasmolderjsijbersmverhoyeAudekerkeavdlinde2008, title = {Functional magnetic resonance imaging in zebra finch discerns the neural substrate involved in segregation of conspecific song from background noise}, journal = {Journal of Neurophysiology}, volume = {99}, year = {2008}, month = {November}, pages = {931-938}, author = {T. Boumans and C. Vignal and Alain Smolders and Jan Sijbers and Marleen Verhoye and Johan Van Audekerke and Annemie Van Der Linden} } @article {1265, title = {Investigating morphological changes in treated vs. untreated stone building materials by x-ray micro-CT}, journal = {Analytical and Bioanalytical Chemistry}, volume = {391}, year = {2008}, month = {6/2008}, pages = {1343 - 1350}, issn = {1618-2642}, doi = {10.1007/s00216-008-1946-7}, author = {Bugani, Simone and Camaiti, Mara and Morselli, Luciano and Elke Van de Casteele and Janssens, Koen} } @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} } @conference {thuysmanBernatGlabbeekjsijbersGielenBortier2008, title = {Left-Right and Gender Analysis of The Human Clavicle, A Problem in Developing an Anatomical Plate?}, year = {2008}, month = {September}, pages = {101}, address = {Brugge, Belgium}, author = {Toon Huysmans and Amit Bernat and Francis Van Glabbeek and Jan Sijbers and Jan L Gielen and H. Bortier} } @inproceedings {BernatthuysmanGlabbeekjsijbersBortierGielen2008, title = {Morphometric Study of the Human Clavicle for the Development of an Anatomical Plate}, booktitle = {54th Annual Meeting of the Orthopaedic Research Society}, year = {2008}, month = {March}, address = {San Francisco, Ca, United States}, author = {Amit Bernat and Toon Huysmans and Francis Van Glabbeek and Jan Sijbers and H. Bortier and Jan L Gielen} } @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 {rpinhoBatenburgjsijbers2008, title = {Seeing Through the Window: Pre-fetching Strategies for Out-of-core Image Processing Algorithms}, booktitle = {Proceedings of SPIE Medical Imaging}, volume = {6919}, year = {2008}, month = {February}, publisher = {SPIE}, organization = {SPIE}, address = {San Diego, CA, USA}, doi = {doi:10.1117/12.769423}, author = {R{\^o}mulo Pinho and Kees Joost Batenburg and Jan Sijbers} } @inproceedings {wvaarlejbatenbujsijbers2008, title = {Threshold Selection for Segmentation of Dense Objects in Tomograms}, booktitle = {International Symposium on Visual Computing}, series = {Lecture Notes on Computer Science}, volume = {5358}, year = {2008}, month = {December}, pages = {700-709}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Berlin Heidelberg}, author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}, editor = {G. Bebis} } @inproceedings {1294, title = {X-ray computed tomography as a non-destructive tool for stone conservation}, booktitle = {9th International Conference on NDT of Art}, year = {2008}, author = {Bugani, Simone and Camaiti, Mara and Morselli, Luciano and Elke Van de Casteele and Cloetens, Peter and Janssens, Koen} } @conference {1296, title = {X-ray microtomography as an imaging tool in cultural heritage}, year = {2008}, author = {Elke Van de Casteele and Bugani, Simone and Annemie Van Der Linden and Janssens, Koen} } @proceedings {-Blanc-TalonPhilipsPopescupscheund2007, title = {ACIVS 2007, Advanced Concepts for Intelligent Vision Systems}, volume = {4678}, year = {2007}, pages = {1-1095}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu and Paul Scheunders} } @inproceedings {Batenburgjsijbers2007, title = {Automatic multiple threshold scheme for segmentation of tomograms}, booktitle = {Proceedings of SPIE Medical Imaging: Physics of Medical Imaging}, year = {2007}, month = {February}, address = {San Diego, CA, USA}, author = {Kees Joost Batenburg and Jan Sijbers}, editor = {Michael J. Flynn, Jiang Hsieh} } @inproceedings {jbatenbujsijbers2007, title = {DART: a fast heuristic algebraic reconstruction algorithm for discrete tomography}, booktitle = {Proceedings of the IEEE International Conference on Image Processing (ICIP)}, year = {2007}, month = {September}, address = {San Antonio, Texas, USA}, doi = {10.1109/ICIP.2007.4379972}, author = {Kees Joost Batenburg 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 {1264, title = {Investigation on porosity changes of Lecce stone due to conservation treatments by means of x-ray nano- and improved micro-computed tomography: preliminary results}, journal = {X-Ray Spectrometry}, volume = {36}, year = {2007}, month = {09/2007}, pages = {316 - 320}, issn = {00498246}, doi = {10.1002/(ISSN)1097-453910.1002/xrs.v36:510.1002/xrs.976}, author = {Bugani, Simone and Camaiti, Mara and Morselli, Luciano and Elke Van de Casteele and Janssens, Koen} } @inproceedings {aleemanswvheckeLebelWalkerjsijbersBeaulieu2007, title = {A model based approach for voxelwise analysis of multi-subject diffusion tensor data}, booktitle = {Joint Annual Meeting ISMRM-ESMRMB}, year = {2007}, address = {Berlin}, author = {Alexander Leemans and Wim Van Hecke and C. Lebel and L. Walker and Jan Sijbers and C. Beaulieu} } @article {BalsjbatenbuVerbeeckjsijbersTendeloo2007, title = {Quantitative three-dimensional reconstruction of catalyst particles for bamboo-like carbon nanotubes}, journal = {Nano Letters}, volume = {7}, number = {12}, year = {2007}, pages = {3669-3674}, doi = {10.1021/nl071899m}, author = {Sara Bals and Kees Joost Batenburg and Jo Verbeeck and Jan Sijbers and Van Tendeloo, Gustaaf} } @inproceedings {1293, title = {X-ray microtomography as a non-destructive tool for stone characterization in a conservation study}, booktitle = {4th ICNDT Hellenic Society}, year = {2007}, author = {Elke Van de Casteele and Bugani, Simone and Camaiti, Mara and Morselli, Luciano and Janssens, Koen} } @proceedings {-Blanc-TalonPhilipsPopescupscheund2006, title = {ACIVS 2006, Advanced Concepts for Intelligent Vision Systems}, volume = {4179}, year = {2006}, pages = {1-1224}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu and Paul Scheunders} } @inproceedings {Batenburgjsijbersevdcaste2006, title = {Automatic multiple threshold scheme for segmentation of tomograms}, booktitle = {Proceedings of the Biomedical Engineering IEEE/EMBS Benelux Symposium}, volume = {2}, year = {2006}, month = {December}, pages = {143-146}, address = {Brussels, Belgium}, author = {Kees Joost Batenburg and Jan Sijbers and Elke Van de Casteele} } @inproceedings {Batenburgjsijbers2006, title = {Discrete tomography from micro-CT data: application to the mouse trabecular bone structure}, booktitle = {Proceedings of SPIE Medical Imaging: Physics of Medical Imaging}, volume = {6142}, year = {2006}, month = {February}, pages = {1325-1335}, address = {San Diego, CA, USA}, doi = {https://doi.org/10.1117/12.652603}, author = {Kees Joost Batenburg and Jan Sijbers}, editor = {Michael J. Flynn, Jiang Hsieh} } @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} } @conference {1300, title = {Investigation on Lecce stone porosity by means of micro and nano X-ray tomography}, year = {2006}, author = {Bugani, Simone and Camaiti, Mara and Morselli, Luciano and Janssens, Koen and Elke Van de Casteele} } @inproceedings {BertelsthuysmanjsijbersVerdonkParizel2006, title = {Multi-scale registration of spherical parametrizations of the human cortex}, booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {89}, address = {Warsaw, Poland}, author = {J. Bertels and Toon Huysmans and Jan Sijbers and B. Verdonk and Paul M Parizel} } @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 {thuysmanBernatjsijbersParizelGlabbeekVerdonk2006, title = {Shape Analysis of the Human Clavicle for the Development of a Set of osteosynthesis Plates}, booktitle = {Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium}, year = {2006}, month = {December}, pages = {128-129}, address = {Brussels, Belgium}, author = {Toon Huysmans and Amit Bernat and Jan Sijbers and Paul M Parizel and Francis Van Glabbeek and B. Verdonk} } @inproceedings {Batenburgjsijbers2006, title = {Trabecular bone reconstruction from micro-CT data using discrete tomography}, booktitle = {Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium)}, year = {2006}, month = {March}, pages = {65-69}, address = {Antwerp, Belgium}, author = {Kees Joost Batenburg and Jan Sijbers} } @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} } @proceedings {-Blanc-TalonPhilipsPopescupscheund2005, title = {ACIVS 2005, Advanced Concepts for Intelligent Vision Systems}, volume = {3708}, year = {2005}, pages = {1-725}, publisher = {Springer}, author = {J Blanc-Talon and Wilfried Philips and D Popescu 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 {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} } @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} } @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 {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 {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 {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 {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 {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 {jsijbersVanrumsteHoeyBoonmverhoyeavdlindedvandyck2000, title = {Automatic detection of EEG electrode markers on 3D MR data}, booktitle = {SPIE Medical Imaging: Image Processing}, volume = {3979}, year = {2000}, month = {February}, pages = {1476-1481}, address = {San Diego CA, USA}, author = {Jan Sijbers and B. Vanrumste and G. Van Hoey and P. Boon and Marleen Verhoye and Annemie Van Der Linden and Dirk Van Dyck}, editor = {Kenneth M. Hanson} } @article {jsijbersVanrumsteHoeyBoonmverhoyeavdlindedvandyck2000, title = {Automatic localization of EEG electrode markers within 3D MR data}, journal = {Magnetic Resonance Imaging}, volume = {18}, number = {4}, year = {2000}, pages = {485-488}, doi = {https://doi.org/10.1016/S0730-725X(00)00121-1}, author = {Jan Sijbers and B. Vanrumste and G. Van Hoey and P. Boon and Marleen Verhoye and Annemie Van Der Linden and Dirk Van Dyck} } @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} } @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} } @mastersthesis {1277, title = {Peak Characterization using Parameter Estimation Methods}, year = {1999}, school = {University of Antwerp}, type = {PhD thesis}, address = {Antwerp}, author = {E. Bettens} } @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} } @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} } @article {mverhoyeavdlindeAudekerkejsijbersEensBalthazart1998, title = {Imaging birds in a bird cage: in-vivo FSE 3D MRI of bird brain}, journal = {MAGMA: Magnetic Resonance Materials in Physics, Biology and Medicine}, volume = {6}, number = {1}, year = {1998}, month = {August}, pages = {22-27}, author = {Marleen Verhoye and Annemie Van Der Linden and Johan Van Audekerke and Jan Sijbers and M. Eens and J. Balthazart} } @article {Baillieuxpscheund1998, title = {On-line determination of the velocity of simultaneously moving organisms by image analysis for the detection of sublethal toxicity}, journal = {Water Research}, volume = {32}, number = {4}, year = {1998}, pages = {1027-1034}, author = {M. Baillieux and Paul Scheunders} } @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} } @article {ebettenspscheunddvandyckMoensOsta1997, title = {Computer Analysis of Two-Dimensional Electrophoresis Gels : A New Segmentation and Modeling Algorithm}, journal = {Electrophoresis}, volume = {18}, year = {1997}, pages = {792-798}, doi = {10.1002/elps.1150180523}, author = {E. Bettens and Paul Scheunders and Dirk Van Dyck and L. Moens and P. Van Osta} } @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} } @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 {gvdwouweVautrotpscheundslivensdvandyckBonnet1997, title = {Rotation-invariant texture segmentation using continuous wavelets}, booktitle = {Proc. 2-nd IEEE Symposium on applications of time-frequency and time-scale methods , Coventry, UK, 27-29/9}, year = {1997}, author = {G. Van de Wouwer and P. Vautrot and Paul Scheunders and S. Livens and Dirk Van Dyck and N. Bonnet} } @inproceedings {ebettenspscheundjsijbersdvandyckMoens1996, title = {Automatic segmentation and modeling of two-dimensional electrophoresis gels}, booktitle = {Proceedings of IEEE International Conference on Image Processing}, volume = {2}, year = {1996}, month = {September}, pages = {665-668}, address = {Lausanne, Switserland}, author = {E. Bettens and Paul Scheunders and Jan Sijbers and Dirk Van Dyck and L. Moens} } @article {jsijberspscheundBonnetdvandyckeraman1996, title = {Quantification and improvement of the signal-to-noise ratio in a magnetic resonance image acquisition procedure}, journal = {Magnetic Resonance Imaging}, volume = {14}, number = {10}, year = {1996}, pages = {1157-1163}, doi = {10.1016/S0730-725X(96)00219-6}, author = {Jan Sijbers and Paul Scheunders and N. Bonnet and Dirk Van Dyck and Erik Raman} } @article {slivenspscheundgvdwouwedvandyckSmetsWinkelmansBogaerts1996, title = {A texture analysis approach to corrosion image classification}, journal = {Microscopy, Microanalysis, Microstructures}, volume = {7}, year = {1996}, pages = {1-10}, author = {S. Livens and Paul Scheunders and G. Van de Wouwer and Dirk Van Dyck and H. Smets and J. Winkelmans and W. Bogaerts} } @inproceedings {gvdwouwepscheunddvandyckBodtWuytsHeyning1996, title = {Wavelet-FILVQ classifier for speech analysis}, booktitle = {Proc. ICPR{\textquoteright}96 Internat. Conference on Pattern Recognition , D, pp. 214-218, Vienna, august 25-30}, year = {1996}, pages = {214-218}, author = {G. Van de Wouwer and Paul Scheunders and Dirk Van Dyck and M. De Bodt and Floris L Wuyts and Paul H Van de Heyning} } @article {slivenspscheundgvdwouwedvandyckSmetsWinkelmansBogaerts1995, title = {Classification of corrosion images by wavelet signatures and LVQ networks}, journal = {Lecture Notes in Computer Science}, volume = {970}, year = {1995}, pages = {538-543}, author = {S. Livens and Paul Scheunders and G. Van de Wouwer and Dirk Van Dyck and H. Smets and J. Winkelmans and W. Bogaerts} }