@article {2431, title = {Physiological cerebrospinal fluid interactions between brain and eye structures are altered after long-duration spaceflight}, journal = {Experimental Physiology}, year = {2026}, doi = {http://doi.org/10.1113/EP093112}, author = {Ge Tang and Steven Jillings and Ben Jeurissen and Elena Tomilovskaya and Inna Nosikova and Alexandra Riabova and Ekaterina V. Pechenkova and Petrovichev, Victor and Ilya Rukavishnikov and Stefan Sunaert and Paul M Parizel and Lyudmila Makovskaya and Valentin Sinitsyn and Jan Sijbers and Jitka Annen and Steven S L Laureys and Angelique Van Ombergen and Seyed-Ahmad Ahmadi and Floris L Wuyts and Peter zu Eulenburg} } @article {2406, title = {Harmonization of diffusion MRI on healthy subjects using NeuroCombat and LongCombat: a B-Q MINDED Brain Intra-and Inter-Scanner Study}, journal = {Frontiers in Neuroscience}, volume = {19}, year = {2025}, doi = {10.3389/fnins.2025.1591169}, author = {Maira Siqueira Pinto and Vincenzo Anania and Roberto Paolella and Celine Smekens and Thibo Billiet and Thomas Janssens and Arnold Jan den Dekker and Sijbers, Jan and Pieter-Jan Guns and Pieter Van Dyck} } @article {2426, title = {Leveraging Hand-Crafted Radiomics on Multicenter FLAIR MRI for Predicting Disability Worsening in People with Multiple Sclerosis}, journal = {Front. Neurosci.}, volume = {19}, year = {2025}, doi = {https://doi.org/10.3389/fnins.2025.1610401}, author = {Hamza Khan and Diana Giraldo and Henry C. Woodruff and Lorin Werthen-Brabants and Shruti Atul Mali and Sina Amirrajab and Edward De Brouwer and Veronica Popescu and Bart Van Wijmeersch and Oliver Gerlach and Jan Sijbers and Liesbet M. Peeters and Philippe Lambin} } @article {2421, title = {A Spectral-Spatial Attention Network for Hyperspectral Unmixing}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {63}, year = {2025}, pages = {1-15}, abstract = {Hyperspectral unmixing, an essential and fundamental task in remote sensing, focuses on estimating endmembers (spectrally pure components) and their fractional abundances within each mixed pixel of a hyperspectral image. With the advent of deep learning (DL), the field of hyperspectral unmixing has made significant progress. Among DL approaches, autoencoder-based models have shown promising results. However, most unmixing methods estimate the endmembers by the weights of the linear layers in the decoder of their networks, making their performance highly dependent on weight initialization. Moreover, noise is not explicitly accounted for in most recent methods that use spectral angle distance (SAD) loss. To avoid the initialization problems, we developed an innovative inversion strategy to directly estimate the endmembers. Moreover, to optimally account for noise, an end-to-end network is proposed, which integrates both denoising and unmixing. Finally, for an improved feature extraction, a novel spectral-spatial attention module (SSAM) is integrated into the network. Extensive experiments on synthetic and three real datasets show that the proposed method significantly and consistently outperforms the compared state-of-the-art methods. The full code is available at https://github.com/xuanwentao for public evaluation.}, keywords = {Attention module, autoencoder, Autoencoders, autonomous unmixing module (AUM), Convolutional neural networks, Data mining, Decoding, deep denoising module (DDM), Feature extraction, Hyperspectral imaging, Hyperspectral unmixing, image reconstruction, Loss measurement, Neural networks, Noise reduction}, doi = {10.1109/TGRS.2025.3576479}, author = {Tao, Xuanwen and Koirala, Bikram and Rasti, Behnood and Plaza, Antonio and Scheunders, Paul} } @inproceedings {2418, title = {About rapid phase-wrapping in terahertz phase contrast imaging}, booktitle = {SPIE}, volume = {13141}, year = {2024}, pages = {69-73}, abstract = {Terahertz (THz) imaging has emerged as a powerful technique in diverse fields, ranging from medical diagnostics to material characterization. Due to its lower frequency, compared to x-ray-based techniques, THz imaging provides an alternative view into the internal structures of samples composed of low-density materials. Notably, phase contrast imaging is advantageous as it generally exhibits reduced distortion from refraction and reflection losses compared to attenuation contrast. However, in the course of THz phase measurements, a fresh issue arises. Due to the relatively wide beam shape of THz imaging combined with rapid phase wrapping, a new type of artifact emerges, posing a significant hindrance to the accuracy and reliability of the imaging process. This paper explores the intricate interplay between beam shape dynamics and phase-wrapping mechanisms in THz imaging systems, unraveling the source of the artifacts that arise from this phenomenon.}, doi = {https://doi.org/10.1117/12.3027665}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410F/About-rapid-phase-wrapping-in-terahertz-phase-contrast-imaging/10.1117/12.3027665.short}, author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @article {2323, title = {CAD-ASTRA: A versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox}, journal = {Optics Express}, volume = {32}, year = {2024}, pages = {3425-3439}, doi = {https://doi.org/10.1364/OE.498194}, author = {Pavel Paramonov and Nicholas Francken and Jens Renders and Domenico Iuso and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers} } @inproceedings {2419, title = {Coherent detection terahertz imaging with a continuous wave source}, booktitle = {SPIE}, volume = {13141}, year = {2024}, pages = {63-68}, abstract = {The unique properties of terahertz (THz) radiation, coupled with its non-ionizing nature, enable high-contrast imaging of soft materials with less stringent safety precautions than those required for x-ray systems. In this study, we introduce novel methods for THz imaging using a system that employs two photoconductive antennas (PCAs): one as a Continuous-Wave (CW) source and the other as a coherent detector. To enable precise multiband imaging with high frequency resolution, a fiber stretcher for rapid phase modulation was included. This system allows for the registration of two types of imaging contrasts: light attenuation and phase shift. We outline methods for extracting these contrasts and evaluate the system{\textquoteright}s capabilities through experiments involving various materials and frequencies. Furthermore, its application in computed tomography is demonstrated. To the best of our knowledge, this is the first application of a CW setup based on PCAs for non-destructive inspection and imaging of concealed objects.}, doi = {https://doi.org/10.1117/12.3027653}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410E/Coherent-detection-terahertz-imaging-with-a-continuous-wave-source/10.1117/12.3027653.short}, author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @article {2329, title = {Edge illumination x-ray phase contrast simulations using the CAD-ASTRA toolbox}, journal = {Optics Express}, volume = {32}, year = {2024}, pages = {10005-10021}, doi = {10.1364/OE.516138}, url = {https://opg.optica.org/oe/abstract.cfm?doi=10.1364/OE.516138}, author = {Nicholas Francken and Jonathan Sanctorum and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @inproceedings {2350, title = {High-resolution tiled X-ray cone-beam CT using the ASTRA toolbox}, booktitle = {13th Conference on Industrial Computed Tomography (iCT) 2024}, year = {2024}, month = {03/2024}, address = {School of Engineering, Wels Campus, Austria}, abstract = {Dealing with large and/or elongated objects presents a challenge in micro computed tomography ({\textmu}CT). In conventional CT, the necessity for the X-ray beam to fully cover the scanned object which has to remain well within the detector boundaries is essential to avoid region-of-interest artifacts in the reconstructed images. Consequently, the magnification of the object and thereby the spatial resolution are limited by the physical dimensions and degrees of freedom of the imaging system. A possible way to increase the magnification and thus the resolution of a {\textmu}CT image is to perform a tiled scan of the object. In this paper, we propose an iterative reconstruction approach that yields a high-resolution image from such a tiled CT scan. The approach utilizes the ASTRA toolbox, leveraging its key features: the vector-based definition of projection geometry and the linear tomography operators. Our simulations demonstrate that the proposed approach achieves higher resolution through increased magnification.}, keywords = {cone beam, iterative reconstruction, micro computed tomography, X-ray tomography}, isbn = {1435-4934}, doi = {10.58286/29258 }, author = {Pavel Paramonov and Joaquim G. Sanctorum and Domenico Iuso and Jan Sijbers and Jan De Beenhouwer} } @article {2382, title = {A New Dual-Feature Fusion Network for Enhanced Hyperspectral Unmixing}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2024}, pages = {1-1}, keywords = {Accuracy, dual-feature fusion, Estimation, Feature extraction, Hyperspectral imaging, Hyperspectral unmixing, image reconstruction, Noise reduction, Reflectivity, Scattering, similarity, Transformers, Transforms, unmixing module}, doi = {10.1109/TGRS.2024.3505292}, author = {Tao, Xuanwen and Koirala, Bikram and Plaza, Antonio and Scheunders, Paul} } @article {2358, title = {PACS: Projection-driven with Adaptive CADs X-ray Scatter compensation for additive manufacturing inspection}, journal = {Precision Engineering}, volume = {90}, year = {2024}, pages = {108-121}, doi = {https://doi.org/10.1016/j.precisioneng.2024.08.006}, author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers} } @article {2364, title = {Perceptual super-resolution in multiple sclerosis MRI}, journal = {Frontiers in Neuroscience}, volume = {18}, year = {2024}, doi = {10.3389/fnins.2024.1473132}, author = {Diana Giraldo and Hamza Khan and Gustavo Pineda and Liang, Zhihua and Alfonso Lozano and Bart Van Mijweersch and Henry C. Woodruff and Philippe Lambin and Romero, Eduardo and Liesbet M. Peeters and Jan Sijbers} } @article {2336, title = {Practical multi-mesh registration for few-view poly-chromatic X-ray inspection}, journal = {Journal of Non-destructive Testing}, volume = {43}, year = {2024}, chapter = {63}, doi = {10.1007/s10921-024-01071-y}, author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers} } @article {2256, title = {ADEPT: Accurate Diffusion EPI with multi-contrast shoTs}, journal = {Magnetic Resonance in Medicine}, volume = {89}, year = {2023}, pages = {396-410}, doi = {10.1002/mrm.29398}, author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Stefan Klein and Johan Van Audekerke and Verhoye, Marleen and Arnold Jan den Dekker and Jan Sijbers} } @inproceedings {2287, title = {A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations}, booktitle = {45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society}, year = {2023}, author = {Nicholas Francken and Jonathan Sanctorum and Jens Renders and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @inproceedings {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} } @article {2297, title = {dtiRIM: A generalisable deep learning method for diffusion tensor imaging}, journal = {Neuroimage}, volume = {269}, year = {2023}, chapter = {119900}, doi = {10.1016/j.neuroimage.2023.119900}, author = {Emanoel Ribeiro Sabidussi and Stefan Klein and Ben Jeurissen and Dirk H J Poot} } @article {2305, title = {Efficient iterative reconstruction with beam shape compensation for THz computed tomography}, journal = {Applied Optics}, volume = {62}, year = {2023}, month = {April 14, 2023}, pages = {F31-F40}, chapter = {F31}, abstract = {Terahertz (THz) computed tomography is an emerging nondestructive and non-ionizing imaging method. Most THz reconstruction methods rely on the Radon transform, originating from x-ray imaging, in which x rays propagate in straight lines. However, a THz beam has a finite width, and ignoring its shape results in blurred reconstructed images. Moreover, accounting for the THz beam model in a straightforward way in an iterative reconstruction method results in extreme demands in memory and in slow convergence. In this paper, we propose an efficient iterative reconstruction that incorporates the THz beam shape, while avoiding the above disadvantages. Both simulation and real experiments show that our approach results in improved resolution recovery in the reconstructed image. Furthermore, we propose a suitable preconditioner to improve the convergence speed of our reconstruction.}, keywords = {Beam shaping, computed tomography, Image quality, image reconstruction, THz imaging}, doi = {https://doi.org/10.1364/AO.482511}, url = {https://opg.optica.org/viewmedia.cfm?r=1\&rwjcode=ao\&uri=ao-62-17-F31\&seq=0}, author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @inproceedings {2299, title = {Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations}, booktitle = {IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy}, year = {2023}, author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @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} } @article {2264, title = {Fast and accurate pose estimation of additive manufactured objects from few X-ray projections}, journal = {Expert Systems With Applications}, volume = {213}, year = {2023}, pages = {1-10}, doi = {https://doi.org/10.1016/j.eswa.2022.118866}, author = {Alice Presenti and Liang, Zhihua and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer} } @article {2270, title = {Prolonged microgravity induces reversible and persistent changes on human cerebral connectivity}, journal = {Communications Biology}, volume = {6}, year = {2023}, doi = {https://doi.org/10.1038/s42003-022-04382-w}, author = {Steven Jillings and Ekaterina V. Pechenkova and Elena Tomilovskaya and Ilya Rukavishnikov and Ben Jeurissen and Angelique Van Ombergen and Nosikova, Inna and Alena Rumshiskaya and Liudmila Litvinova and Annen, Jitka and Chloe De Laet and Catho Schoenmaekers and Jan Sijbers and Petrovichev, Victor and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and zu Eulenburg, P and Steven S L Laureys and Athena Demertzi and Floris L Wuyts} } @article {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} } @article {2286, title = {Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study}, journal = {Journal of Neurotrauma}, volume = {40}, year = {2023}, pages = {1317-1338}, doi = {https://doi.org/10.1089/neu.2022.0365}, author = {Maira Siqueira Pinto and Stefan Winzeck and Evgenios N. Kornaropoulos and Sophie Richter and Roberto Paolella and Marta M. Correia and Ben Glocker and Guy Williams and Anne Vik and Jussi Posti and Asta Kristine H{\r a}berg and Jonas Stenberg and Pieter-Jan Guns and Arnold Jan den Dekker and David K. Menon and Jan Sijbers and Pieter Van Dyck and Virginia F. J. Newcombe} } @mastersthesis {2280, title = {3D X-ray radiography-based inspection of manufactured objects}, volume = {PhD}, year = {2022}, type = {PhD thesis}, author = {Alice Presenti} } @article {2236, title = {Automatic anomaly detection from X-ray images based on autoencoder}, journal = {Nondestructive Testing and Evaluation}, volume = {37}, year = {2022}, doi = {10.1080/10589759.2022.2074415}, author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer} } @article {2216, title = {Brain Connectometry Changes in Space Travelers After Long-Duration Spaceflight}, journal = {Front. Neural Circuits}, volume = {16}, year = {2022}, doi = {https://doi.org/10.3389/fncir.2022.815838}, author = {Andrei Doroshin and Steven Jillings and Ben Jeurissen and Elena Tomilovskaya and Ekaterina V. Pechenkova and Nosikova, Inna and Alena Rumshiskaya and Liudmila Litvinova and Ilya Rukavishnikov and Chloe De Laet and Catho Schoenmaekers and Jan Sijbers and Steven S L Laureys and Petrovichev, Victor and Angelique Van Ombergen and Jitka Annen and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and zu Eulenburg, Peter and Karol Osipowicz and Floris L Wuyts} } @inproceedings {2194, title = {CNN-based pose estimation from a single X-ray projection for 3D inspection of manufactured objects}, booktitle = {11th Conference on Industrial Computed Tomography}, year = {2022}, author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer} } @article {2193, title = {Discrete Terahertz tomography: a simulation study}, journal = {e-Journal of Nondestructive Testing}, volume = {27}, year = {2022}, issn = {1435-4934}, doi = {doi.org/10.58286/26608}, author = {Jana Christopher and Lars-Paul Lumbeeck and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers} } @conference {2269, title = {Edge Illumination Phase Contrast Simulations Using the OptiX GPU Ray Tracing Engine}, year = {2022}, author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @article {2215, title = {The effect of prolonged Spaceflight on Cerebrospinal Fluid and Perivascular Spaces of Astronauts and Cosmonauts}, journal = {PNAS}, volume = {119}, year = {2022}, chapter = {e2120439119}, doi = {https://doi.org/10.1073/pnas.2120439119}, author = {Giuseppe Barisano and Farshid Sepehrband and Heather R. Collins and Steven Jillings and Ben Jeurissen and Andrew J. Taylor and Catho Schoenmaekers and Chloe De Laet and Ilya Rukavishnikov and Inna Nosikova and Alena Rumshiskaya and Jitka Annen and Jan Sijbers and Steven S L Laureys and Angelique Van Ombergen and Petrovichev, Victor and Valentin Sinitsyn and Ekaterina V. Pechenkova and Alexey Grishin and Peter zu Eulenburg and Meng Law and Stefan Sunaert and Paul M. Parizel and Elena Tomilovskaya and Donna Roberts and Floris L Wuyts} } @inproceedings {2240, title = {Efficient X-ray projection of triangular meshes based on ray tracing and rasterization}, booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV }, volume = {12242}, year = {2022}, pages = {122420W }, doi = {https://doi.org/10.1117/12.2633448}, author = {Pavel Paramonov and Jens Renders and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers} } @inproceedings {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 {2208, title = {Identification of corrosion minerals usning shortwave infrared hyperspectral imaging}, journal = {Sensors}, volume = {22}, year = {2022}, pages = {407}, abstract = {In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900{\textendash}1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time. }, author = {Thomas De Kerf and G. Pipintakos and Zohreh Zahiri and Steve Vanlanduit and Paul Scheunders} } @article {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 {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} } @article {2275, title = {To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging}, journal = {Frontiers in Neuroscience}, year = {2022}, pages = {1-18}, doi = {https://doi.org/10.3389/fnins.2022.1044510}, author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @inproceedings {2186, title = {3D THz Tomography Incorporating the Beam Shape}, booktitle = {2021 OSA Imaging and Applied Optics Congress}, year = {2021}, doi = {10.1364/AIS.2021.JTu5A.36}, author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @conference {2184, title = {Accelerated multi-shot diffusion weighted imaging with joint estimation of diffusion and phase parameters}, volume = {34}, year = {2021}, pages = {S57-S58}, doi = {10.1007/s10334-021-00947-8}, author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Johan Van Audekerke and Marleen Verhoye and Arnold Jan den Dekker and Jan Sijbers} } @article {2079, title = {Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing}, journal = {Magnetic Resonance in Medicine}, volume = {85}, year = {2021}, pages = {1397-1413}, doi = {https://doi.org/10.1002/mrm.28520}, author = {Maarten Naeyaert and Jan Aelterman and Vladimir Golkov and Daniel Cremers and Aleksandra Pizurica and Jan Sijbers and Marleen Verhoye} } @article {2143, title = {Associations between different white matter properties and reward-based performance modulation}, journal = {Brain Structure and Function}, year = {2021}, month = {Apr-02-2021}, issn = {1863-2653}, doi = {10.1007/s00429-021-02222-x}, url = {https://link.springer.com/content/pdf/10.1007/s00429-021-02222-x.pdf}, author = {Park, Haeme R. P. and Verhelst, Helena and Quak, Michel and Ben Jeurissen and Krebs, Ruth M.} } @inproceedings {2201, title = {CNN-based Pose Estimation of Manufactured Objects During Inline X-ray Inspection}, booktitle = {2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)}, year = {2021}, abstract = {X-ray Computed Tomography (CT) is a nondestructive technique widely used for inspection of manufactured objects generated from a reference computer-aided-design (CAD) representation. In a conventional CT inspection framework, a volumetric reconstruction is computed from a large number of X-ray projections of the object. Afterwards, a surface is extracted, aligned and compared to the CAD model. For an accurate comparison, a high-resolution reconstruction is needed, requiring hundreds of projections, making this procedure not suitable for real-time inspection. In contrast to CT-based inspection, radiograph-based inspection only requires a few radiographs that then can be compared with simulated projections from the reference CAD model. For an effective comparison, however, an accurate 3D pose estimation of the object and consequent alignment between the measured object and the reference model are crucial. In this paper, we present an inline projection-based 3D pose estimation framework using convolutional neural networks (CNNs). Through realistic simulation experiments, we show that, with only two projections, estimation of the pose of the object is possible at the resolution of the acquisition system.}, author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer} } @article {2135, title = {Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil{\textendash}water three phase flows}, journal = {Measurement}, volume = {168}, year = {2021}, chapter = {108427}, abstract = {In this investigation, a fan-beam photon attenuation based system, including one X-ray tube and two sodium iodide crystal detectors, combined with group method of data handling (GMDH) neural network is proposed to recognize type of flow regime and predict gas-oil{\textendash}water volume fractions of a three phase flow. One GMDH neural network was considered for recognizing flow patterns and two GMDH networks were implemented to predict the volume fractions. The recorded photon energy spectra from the two sodium iodide detectors were defined as the inputs of the three GMDH neural networks. The type of flow pattern and volume fractions were the output obtained from the first and the other two GMDH neural networks, respectively. Through the application of the proposed methodology, all of the flow patterns were recognized correctly except one single case. The volume fraction was also predicted with RMS error of less than 3.1.}, doi = {10.1016/j.measurement.2020.108427}, author = {Mohammadmehdi Roshani and Giang Phan and Gholam Hossein Roshani and Robert Hanus and Enrico Corniani and Ehsan Nazemi} } @inproceedings {2159, title = {Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error}, booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine}, year = {2021}, abstract = {In multi-slice super-resolution reconstruction (MS-SRR), a high resolution image, referred to as SRR image, is estimated from a series of multi-slice images with a low through-plane resolution. This work proposes a framework based on the Bayesian mean squared error of the Maximum A Posteriori estimator of a SRR image to compare the accuracy and precision of two commonly adopted MR acquisition strategies in MS-SRR. The first strategy consists in acquiring a set of multi-slice images, where each image is shifted in the through-plane direction by a different, sub-pixel distance. The latter consists in acquiring a set of multi-slice images, where each image is rotated around the frequency or phase-encoding axis by a different rotation angle. Results show that MS-SRR based on rotated multi-slice images outperforms MS-SRR based on shifted multi-slice images in terms of accuracy, precision and mean squared error of the reconstructed image.}, author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @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 {2171, title = {Dynamic few-view X-ray imaging for inspection of CAD-based objects}, journal = {Expert Systems with Applications}, volume = {180}, year = {2021}, pages = {115012}, keywords = {CAD, Dynamic acquisition, Few-view inspection, Pose estimation, Visibility angles}, issn = {0957-4174}, doi = {https://doi.org/10.1016/j.eswa.2021.115012}, url = {https://www.sciencedirect.com/science/article/pii/S095741742100453X}, author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer} } @article {2137, title = {Evaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline{\textquoteright}s scale layer thickness}, journal = {Alexandria Engineering Journal}, volume = {60}, year = {2021}, abstract = {The main objective of the present research is to combine the effect of scale thickness on the flow pattern and characteristics of two-phase flow that is used in oil industry. In this regard, an intelligent nondestructive technique based on combination of gamma radiation attenuation and artificial intelligence is proposed to determine the type of flow pattern and gas volume percentage in two phase flow independent of petroleum pipeline{\textquoteright}s scale layer thickness. The proposed system includes a dual energy gamma source, composed of Barium-133 and Cesium-137 radioisotopes, and two sodium iodide detectors for recording the transmitted and scattered photons. Support Vector Machine was implemented for regime identification and Multi-Layer Perceptron with Levenberg Marquardt algorithm was utilized for void fraction prediction. Total count in the scattering detector and counts under photo peaks of Barium-133 and Cesium-137 were assigned as the inputs of networks. The results show the ability of presented system to identify the annular regime and measure the void fraction independent of petroleum pipeline{\textquoteright}s scale layer thickness.}, author = {Mohammadmehdi Roshani and Giang T.T. Phan and Gholam Hossein Roshani and Robert Hanus and Trung Duong and Enrico Corniani and Ehsan Nazemi and ElMostafa Kalmouni} } @article {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} } @inproceedings {2189, title = {Multi-contrast multi-shot EPI for accelerated diffusion MRI}, booktitle = {43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society}, year = {2021}, pages = {3869-3872}, doi = {10.1109/EMBC46164.2021.9630069}, author = {Banafshe Shafieizargar and Ben Jeurissen and Dirk H J Poot and Arnold Jan den Dekker and Jan Sijbers} } @inproceedings {2169, title = {Recurrent Inference Machines as Inverse Problem Solvers for MR Relaxometry}, booktitle = { MIDL 2021 - Medical Imaging with Deep Learning}, year = {2021}, author = {Emanoel Ribeiro Sabidussi and Matthan Caan and Shabab Bazrafkan and Arnold Jan den Dekker and Jan Sijbers and Wiro J Niessen and Dirk H J Poot} } @article {2190, title = {Recurrent Inference Machines as inverse problem solvers for MR relaxometry}, journal = {Medical Image Analysis}, volume = {74}, year = {2021}, pages = {1-11}, doi = {https://doi.org/10.1016/j.media.2021.102220}, author = {Emanoel Ribeiro Sabidussi and Stefan Klein and Matthan Caan and Shabab Bazrafkan and Arnold Jan den Dekker and Jan Sijbers and Wiro J Niessen and Dirk H J Poot} } @conference {2181, title = {Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer}, volume = {34}, year = {2021}, pages = {S56-S57}, doi = {10.1007/s10334-021-00947-8}, author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @inproceedings {2187, title = {A study of terahertz beam simulation with ray tracing for computed tomography}, booktitle = {2021 OSA Imaging and Applied Optics Congress}, year = {2021}, doi = {10.1364/AIS.2021.JTu5A.37}, author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan Sijbers and Jan De Beenhouwer} } @inproceedings {2053, title = {Accurate terahertz simulation with ray tracing incorporating beam shape and refraction}, booktitle = {IEEE ICIP }, year = {2020}, pages = {3035-3039}, doi = {10.1109/ICIP40778.2020.9190937}, author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan De Beenhouwer and Jan Sijbers} } @inproceedings {1951, title = {A Comparative Study Between Three Measurement Methods to Predict 3D Body Dimensions Using Shape Modelling}, booktitle = {Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping}, volume = {975}, year = {2020}, pages = {464{\textendash}470}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {In times of online shopping, it is a challenge to select the right size of the desired clothing without fitting it before ordering. Therefore, this study describes three techniques to predict 3D upper body dimensions. The first method used basic personal parameters (gender, age, weight and length), the second technique used also the shoulder width and the last method used a 3D Styku scan to add extra input parameters. The accuracy of the three prediction methods was compared against hand measurements for 17 upper body dimensions of 37 subjects. The Intraclass Correlation Coefficient increases with 11.2\% for the Styku method compared to the other methods. For chest, hip and waist measurements, the basic method is reliable to predict 3D body dimensions and indicate the right size from an existing collection. For more accurate upper body dimensions as needed for producing custom made clothing, a 3D Styku scan can supply the desired input.}, isbn = {978-3-030-20216-3}, doi = {10.1007/978-3-030-20216-3_43}, author = {Peeters, Thomas and Vleugels, Jochen and Stijn Verwulgen and Femke Danckaers and Toon Huysmans and Jan Sijbers and De Bruyne, Guido}, editor = {Di Nicolantonio, Massimo and Rossi, Emilio and Alexander, Thomas} } @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} } @conference {Jillings2020-nb, title = {Diffusion MRI reveals macro- and microstructural changes in cosmonauts{\textquoteright} brains after long-duration spaceflight}, year = {2020}, pages = {4531}, author = {Jillings, S and Angelique Van Ombergen and Tomilovskaya, E and Rumshiskaya, A and Litvinova, L and Nosikova, I and Pechenkova, E and Rukavishnikov, I and Kozlovskaya, I and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Petrovichev, V and Laureys, S and zu Eulenburg, P and Jan Sijbers and Floris L Wuyts and Ben Jeurissen} } @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} } @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 {2074, title = {Macro- and microstructural changes in cosmonauts{\textquoteright} brains after long-duration spaceflight}, journal = {Science Advances}, volume = {6}, year = {2020}, month = {Apr-09-2020}, pages = {eaaz9488}, abstract = {Long-duration spaceflight causes widespread physiological changes, although its effect on brain structure remains poorly understood. In this work, we acquired diffusion magnetic resonance imaging to investigate alterations of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) compositions in each voxel, before, shortly after, and 7 months after long-duration spaceflight. We found increased WM in the cerebellum after spaceflight, providing the first clear evidence of sensorimotor neuroplasticity. At the region of interest level, this increase persisted 7 months after return to Earth. We also observe a widespread redistribution of CSF, with concomitant changes in the voxel fractions of adjacent GM. We show that these GM changes are the result of morphological changes rather than net tissue loss, which remained unclear from previous studies. Our study provides evidence of spaceflight-induced neuroplasticity to adapt motor strategies in space and evidence of fluid shift{\textendash}induced mechanical changes in the brain.}, doi = {10.1126/sciadv.aaz9488}, url = {https://advances.sciencemag.org/content/6/36/eaaz9488}, author = {Jillings, Steven and Angelique Van Ombergen and Tomilovskaya, Elena and Rumshiskaya, Alena and Litvinova, Liudmila and Nosikova, Inna and Pechenkova, Ekaterina and Rukavishnikov, Ilya and Kozlovskaya, Inessa B. and Manko, Olga and Danilichev, Sergey and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Petrovichev, Victor and Laureys, Steven and zu Eulenburg, Peter and Jan Sijbers and Floris L Wuyts and Ben Jeurissen} } @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 {2134, title = {Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products}, journal = {Nuclear Engineering and Technology}, year = {2020}, type = {Research regular paper}, abstract = {It is important for operators of poly-pipelines in petroleum industry to continuously monitor characteristics of transferred fluid such as its type and amount. To achieve this aim, in this study a dual energy gamma attenuation technique in combination with artificial neural network (ANN) is proposed to simultaneously determine type and amount of four different petroleum by-products. The detection system is composed of a dual energy gamma source, including americium-241 and barium-133 radioisotopes, and one 2.54 cm {\texttimes} 2.54 cm sodium iodide detector for recording the transmitted photons. Two signals recorded in transmission detector, namely the counts under photo peak of Americium-241 with energy of 59.5 keV and the counts under photo peak of Barium-133 with energy of 356 keV, were applied to the ANN as the two inputs and volume percentages of petroleum by-products were assigned as the outputs.}, author = {Mohammadmehdi Roshani and Giang Phan and Rezhna Hassan Faraj and Nhut-Huan Phan and Gholam Hossein Roshani and Enrico Corniani and Ehsan Nazemi} } @inproceedings {2054, title = {The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape}, booktitle = {IEEE ICIP}, year = {2020}, pages = {3040-3044}, doi = {10.1109/ICIP40778.2020.9191175}, author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer} } @article {1964, title = {Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI.}, journal = {Front Physiol}, volume = {10}, year = {2019}, pages = {1-23}, abstract = {

The present study reports alterations of task-based functional brain connectivity in a group of 11 cosmonauts after a long-duration spaceflight, compared to a healthy control group not involved in the space program. To elicit the postural and locomotor sensorimotor mechanisms that are usually most significantly impaired when space travelers return to Earth, a plantar stimulation paradigm was used in a block design fMRI study. The motor control system activated by the plantar stimulation involved the pre-central and post-central gyri, SMA, SII/operculum, and, to a lesser degree, the insular cortex and cerebellum. While no post-flight alterations were observed in terms of activation, the network-based statistics approach revealed task-specific functional connectivity modifications within a broader set of regions involving the activation sites along with other parts of the sensorimotor neural network and the visual, proprioceptive, and vestibular systems. The most notable findings included a post-flight increase in the stimulation-specific connectivity of the right posterior supramarginal gyrus with the rest of the brain; a strengthening of connections between the left and right insulae; decreased connectivity of the vestibular nuclei, right inferior parietal cortex (BA40) and cerebellum with areas associated with motor, visual, vestibular, and proprioception functions; and decreased coupling of the cerebellum with the visual cortex and the right inferior parietal cortex. The severity of space motion sickness symptoms was found to correlate with a post- to pre-flight difference in connectivity between the right supramarginal gyrus and the left anterior insula. Due to the complex nature and rapid dynamics of adaptation to gravity alterations, the post-flight findings might be attributed to both the long-term microgravity exposure and to the readaptation to Earth{\textquoteright}s gravity that took place between the landing and post-flight MRI session. Nevertheless, the results have implications for the multisensory reweighting and gravitational motor system theories, generating hypotheses to be tested in future research.

}, issn = {1664-042X}, doi = {10.3389/fphys.2019.00761}, author = {Pechenkova, Ekaterina and Nosikova, Inna and Rumshiskaya, Alena and Litvinova, Liudmila and Rukavishnikov, Ilya and Mershina, Elena and Valentin Sinitsyn and Angelique Van Ombergen and Ben Jeurissen and Jillings, Steven and Laureys, Steven and Jan Sijbers and Grishin, Alexey and Chernikova, Ludmila and Naumov, Ivan and Kornilova, Ludmila and Floris L Wuyts and Tomilovskaya, Elena and Kozlovskaya, Inessa} } @article {1941, title = {Brain ventricular volume changes induced by long-duration spaceflight}, journal = {Proceedings of the National Academy of Sciences}, volume = {116}, year = {2019}, pages = {10531-10536}, abstract = {Long-duration spaceflight induces detrimental changes in human physiology due to microgravity. One example is a cephalic fluid shift. Here, we prospectively investigated the quantitative changes in cerebrospinal fluid (CSF) volume of the brain ventricular regions in space crew by means of a region of interest, observer-independent analysis on structural brain MRI scans. MRI scans were collected before the mission, shortly after and 7 mo after return to Earth. We found a significant increase in lateral and third ventricles at postflight and a trend to normalization at follow-up, but still significantly increased ventricular volumes. The observed spatiotemporal pattern of CSF compartment enlargement and recovery points to a reduced CSF resorption in microgravity as the underlying cause.Long-duration spaceflight induces detrimental changes in human physiology. Its residual effects and mechanisms remain unclear. We prospectively investigated the changes in cerebrospinal fluid (CSF) volume of the brain ventricular regions in space crew by means of a region of interest analysis on structural brain scans. Cosmonaut MRI data were investigated preflight (n = 11), postflight (n = 11), and at long-term follow-up 7 mo after landing (n = 7). Post hoc analyses revealed a significant difference between preflight and postflight values for all supratentorial ventricular structures, i.e., lateral ventricle (mean \% change {\textpm} SE = 13.3 {\textpm} 1.9), third ventricle (mean \% change {\textpm} SE = 10.4 {\textpm} 1.1), and the total ventricular volume (mean \% change {\textpm} SE = 11.6 {\textpm} 1.5) (all P \< 0.0001), with higher volumes at postflight. At follow-up, these structures did not quite reach baseline levels, with still residual increases in volume for the lateral ventricle (mean \% change {\textpm} SE = 7.7 {\textpm} 1.6; P = 0.0009), the third ventricle (mean \% change {\textpm} SE = 4.7 {\textpm} 1.3; P = 0.0063), and the total ventricular volume (mean \% change {\textpm} SE = 6.4 {\textpm} 1.3; P = 0.0008). This spatiotemporal pattern of CSF compartment enlargement and recovery points to a reduced CSF resorption in microgravity as the underlying cause. Our results warrant more detailed and longer longitudinal follow-up. The clinical impact of our findings on the long-term cosmonauts{\textquoteright} health and their relation to ocular changes reported in space travelers requires further prospective studies.}, issn = {0027-8424}, doi = {10.1073/pnas.1820354116}, url = {https://www.pnas.org/content/early/2019/05/01/1820354116}, author = {Angelique Van Ombergen and Steven Jillings and Ben Jeurissen and Tomilovskaya, Elena and Alena Rumshiskaya and Liudmila Litvinova and Nosikova, Inna and Ekaterina V. Pechenkova and Ilya Rukavishnikov and Manko, Olga and Danylichev, Sergey and R{\"u}hl, R. Maxine and Inessa B. Kozlovskaya and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Steven S L Laureys and Jan Sijbers and zu Eulenburg, Peter and Floris L Wuyts} } @inproceedings {2090, title = {CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images}, booktitle = {9th Conference on Industrial Computed Tomography}, year = {2019}, pages = {1-5}, address = {Padova, Italy}, author = {Alice Presenti and Jan Sijbers and Arnold Jan den Dekker and Jan De Beenhouwer} } @article {1934, title = {Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields}, journal = {Remote Sensing}, volume = {11}, year = {2019}, chapter = {624}, abstract = {Classification of hyperspectral images is a challenging task owing to the high dimensionality of the data, limited ground truth data, collinearity of the spectra and the presence of mixed pixels. Conventional classification techniques do not cope well with these problems. Thus, in addition to the spectral information, features were developed for a more complete description of the pixels, e.g., containing contextual information at the superpixel level or mixed pixel information at the subpixel level. This has encouraged an evolution of fusion techniques which use these myriad of multiple feature sets and decisions from individual classifiers to be employed in a joint manner. In this work, we present a flexible decision fusion framework addressing these issues. In a first step, we propose to use sparse fractional abundances as decision source, complementary to class probabilities obtained from a supervised classifier. This specific selection of complementary decision sources enables the description of a pixel in a more complete way, and is expected to mitigate the effects of small training samples sizes. Secondly, we propose to apply a fusion scheme, based on the probabilistic graphical Markov Random Field (MRF) and Conditional Random Field (CRF) models, which inherently employ spatial information into the fusion process. To strengthen the decision fusion process, consistency links across the different decision sources are incorporated to encourage agreement between their decisions. The proposed framework offers flexibility such that it can be extended with additional decision sources in a straightforward way. Experimental results conducted on two real hyperspectral images show superiority over several other approaches in terms of classification performance when very limited training data is available}, keywords = {Classification, decision fusion, Hyperspectral}, doi = {https://doi.org/10.3390/rs11060624}, url = {https://www.mdpi.com/2072-4292/11/6/624}, author = {Vera Andrejchenko and Wenzhi Liao and Wilfried Philips and Paul Scheunders} } @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} } @inproceedings {1945, title = {Dynamic angle selection for few-view X-ray inspection of CAD based objects}, booktitle = {Proc. SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)}, volume = {11072}, year = {2019}, doi = {https://doi.org/10.1117/12.2534894}, author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer} } @article {1963, title = {MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation.}, journal = {Neuroimage}, year = {2019}, month = {2019 Aug 29}, pages = {116137}, abstract = {

MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2019.116137}, author = {Tournier, J-Donald and Smith, Robert and Raffelt, David and Tabbara, Rami and Dhollander, Thijs and Pietsch, Maximilian and Christiaens, Daan and Ben Jeurissen and Yeh, Chun-Hung and Connelly, Alan} } @article {1913, title = {Nonlinear hyperspectral unmixing with graphical models}, journal = {IEEE Transaction on Geoscience and Remote Sensing}, volume = {57}, year = {2019}, pages = {4844-4856}, author = {Rob Heylen and Vera Andrejchenko and Zohreh Zahiri and Mario Parente and Paul Scheunders} } @conference {Wuyts2019-xr, title = {Novel insight on effect and recovery of long-duration spaceflight on the ventricles of the space traveller{\textquoteright}s brain}, volume = {2019}, year = {2019}, pages = {IAC{\textendash}19_A1_2_4_x51230}, publisher = {International Astronautical Federation}, author = {Floris L Wuyts and Jillings, Steven and Angelique Van Ombergen and Ben Jeurissen and Tomilovskaya, Elena and Rumshiskaya, Alena and Litvinova, Liudmila and Nosikova, Inna and Pechenkova, Ekaterina and Rukavishnikov, Ilya and others} } @article {1909, title = {Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks}, journal = {Medical Image Analysis}, volume = {52}, year = {2019}, pages = {56-67}, doi = {https://doi.org/10.1016/j.media.2018.10.009}, author = {Timo Roine and Ben Jeurissen and Daniele Perrone and Jan Aelterman and Wilfried Philips and Jan Sijbers and Alexander Leemans} } @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} } @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 {1908, title = {Brain Tissue{\textendash}Volume Changes in Cosmonauts}, journal = {New England Journal of Medicine}, volume = {379}, year = {2018}, pages = {1678 - 1680}, issn = {0028-4793}, doi = {10.1056/NEJMc1809011}, url = {http://www.nejm.org/doi/10.1056/NEJMc1809011}, author = {Angelique Van Ombergen and Steven Jillings and Ben Jeurissen and Tomilovskaya, Elena and R{\"u}hl, Maxine and Alena Rumshiskaya and Nosikova, Inna and Liudmila Litvinova and Annen, Jitka and Ekaterina V. Pechenkova and Inessa B. Kozlovskaya and Stefan Sunaert and Paul M Parizel and Valentin Sinitsyn and Steven S L Laureys and Jan Sijbers and zu Eulenburg, Peter and Floris L Wuyts} } @inproceedings {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} } @conference {1949, title = {Changes in intrinsic functional brain connectivity after first-time exposure to parabolic flight}, year = {2018}, doi = {10.3389/conf.fphys.2018.26.00017}, author = {Angelique Van Ombergen and Floris L Wuyts and Ben Jeurissen and Jan Sijbers and Floris Vanhevel and Steven Jillings and Paul M Parizel and Stefan Sunaert and Paul H Van de Heyning and Vincent Dousset and Steven S L Laureys and Athena Demertzi} } @article {1817, title = {Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology.}, journal = {Alzheimer{\textquoteright}s Research \& Therapy }, volume = {10}, year = {2018}, pages = {1-16}, doi = {10.1186/s13195-017-0329-8}, author = {Jelle Praet and Nikolay Manyakov and Leacky Muchene and Zhenhua Mai and Vasilis Terzopoulos and Steve De Backer and An Torremans and Pieter-Jan Guns and Tom Van De Casteele and Astrid Bottelbergs and Bianca Van Broeck and Jan Sijbers and Dirk Smeets and Ziv Shkedy and Luc Bijnens and Darrel Pemberton and Mark Schmidt and Annemie Van Der Linden and Marleen Verhoye} } @article {1820, title = {Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach}, journal = {Magnetic Resonance in Medicine}, volume = {80}, year = {2018}, pages = {802-813}, doi = {10.1002/mrm.27075}, author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Floris Vanhevel and Pim Pullens and Paul M Parizel and Arnold Jan den Dekker and Jan Sijbers} } @article {1731, title = {Discrete tomography in an in vivo small animal bone study}, journal = {Journal of Bone and Mineral Metabolism}, volume = {36}, year = {2018}, pages = {40{\textendash}53}, doi = {10.1007/s00774-017-0815-x}, author = {Elke Van de Casteele and Egon Perilli and Wim Van Aarle and Karen Reynolds and Jan Sijbers} } @inproceedings {1870, title = {MRF-based decision fusion for hyperspectral image classification}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, year = {2018}, address = {Valencia, Spain}, abstract = {The high dimensionality of hyperspectral images, the limited availability of ground-truth data as well as the low spatial resolution (causing pixels to contain mixtures of materials) hinder hyperspectral image classification. In this work we propose a novel hyperspectral classification method where we combine the outcome of spectral unmixing with the outcome of a supervised classifier. In particular, we consider fractional abundances obtained from a Sparse Unmixing method along with posterior probabilities acquired from a Multinomial Logistic Regression classifier. Both sources of information are fused using a Markov Random Field framework. We conducted experiments on publicly available real hyperspectral images: Indian Pines and University of Pavia using a very limited number of training samples. Our results indicate that the proposed decision fusion approach significantly improves the classification result over using the individual sources and outperforms the state of the art methods.}, url = {https://www.igarss2018.org/Papers/viewpapers.asp?papernum=2751}, author = {Vera Andrejchenko and Rob Heylen and Wenzhi Liao and Wilfried Philips and Paul Scheunders} } @article {1842, title = {NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping}, journal = {IEEE Transactions on Medical Imaging}, volume = {37}, year = {2018}, pages = {2414 - 2427}, doi = {10.1109/TMI.2018.2833288}, author = {Gabriel Ramos-Llord{\'e}n and Gonzalo Vegas-S{\'a}nchez-Ferrero and Marcus Bj{\"o}rk and Floris Vanhevel and Paul M Parizel and Raul San Jos{\'e} Est{\'e}par and Arnold Jan den Dekker and Jan Sijbers} } @conference {Jeurissen2018-zz, title = {Super-resolution for spherical deconvolution of multi-shell diffusion MRI data}, year = {2018}, pages = {36}, author = {Ben Jeurissen and Ramos-Llord{\'e}n, Gabriel and Floris Vanhevel and Paul M Parizel and Jan Sijbers} } @conference {Van_Dyck2018-st, title = {Super-resolution Reconstruction of Knee MRI}, year = {2018}, pages = {5184}, author = {Pieter Van Dyck and Floris Vanhevel and De Smet, E and Paul M Parizel and Jan Sijbers and Ben Jeurissen} } @article {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} } @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 {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} } @conference {Van_Dyck2017-jo, title = {Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft}, year = {2017}, pages = {377}, author = {Pieter Van Dyck and De Smet, Eline and Froeling, Martijn and Verdonk, Peter and Torfs, Micha{\"e}l and Pim Pullens and Jan Sijbers and Paul M Parizel and Ben Jeurissen} } @article {1744, title = {Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft}, journal = {Journal of Magnetic Resonance Imaging}, volume = {46}, year = {2017}, pages = {1423{\textendash}1432}, doi = {10.1002/jmri.25666}, author = {Pieter Van Dyck and Martijn Froeling and Eline De Smet and Pim Pullens and Micha{\"e}l Torfs and Peter Verdonck and Jan Sijbers and Paul M Parizel and Ben Jeurissen} } @article {1756, title = {The effect of spaceflight and microgravity on the human brain}, journal = {Journal of Neurology}, volume = {246}, year = {2017}, pages = {18-22}, doi = {10.1007/s00415-017-8427-x}, author = {Angelique Van Ombergen and Athena Demertzi and Elena Tomilovskaya and Ben Jeurissen and Jan Sijbers and Inessa B. Kozlovskaya and Paul M Parizel and Paul H Van de Heyning and Stefan Sunaert and Steven S L Laureys and Floris L Wuyts} } @inproceedings {1807, title = {Estimation of the intrinsic dimensionality in hyperspectral imagery via the hubness phenomenon}, booktitle = {LVA ICA 2017, International conference on latent variable analysis and signal separation, Grenoble, France, February 21-23, Lecture Notes in Computer Science}, volume = {10169}, year = {2017}, author = {Rob Heylen and Mario Parente and Paul Scheunders} } @article {1800, title = {Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {55}, year = {2017}, pages = {2191-2200}, author = {Rob Heylen and Mario Parente and Paul Scheunders} } @conference {Giraldo2017-nq, title = {Fixel-Based Analysis of Alzheimer{\textquoteright}s Disease Using Multi-Tissue Constrained Spherical Deconvolution of Multi-Shell Diffusion MRI}, year = {2017}, pages = {400}, author = {Diana Giraldo and Struyfs, Hanne and Raffelt, David and Paul M Parizel and Sebastiaan Engelborghs and Romero, Eduardo and Jan Sijbers and Ben Jeurissen} } @article {1803, title = {Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene}, journal = {IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, volume = {10}, year = {2017}, pages = {3768-3781}, author = {Renbo Luo and Wenzhi Liao and H Zhang and L Zhang and Y Pi and Paul Scheunders and Wilfried Philips} } @article {1802, title = {Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy}, journal = {Remote Sensing}, volume = {9}, year = {2017}, chapter = {266}, author = {Birgen Haest and Jeroen Vanden Borre and Toon Spanhove and Guy Thoonen and Stephanie Delalieux and Kooistra, L. and C A M{\"u}cher and D Paelinckx and Paul Scheunders and Pieter Kempeneers} } @article {1718, title = {High angular resolution diffusion-weighted imaging in mild traumatic brain injury}, journal = {NeuroImage: Clinical}, volume = {13}, year = {2017}, month = {11/2016}, pages = {174 - 180}, abstract = {We sought to investigate white matter abnormalities in mild traumatic brain injury (mTBI) using diffusion-weighted magnetic resonance imaging (DW-MRI). We applied a global approach based on tract-based spatial statistics skeleton as well as constrained spherical deconvolution tractography. DW-MRI was performed on 102 patients with mTBI within two months post-injury and 30 control subjects. A robust global approach considering only the voxels with a single-fiber configuration was used in addition to global analysis of the tract skeleton and probabilistic whole-brain tractography. In addition, we assessed whether the microstructural parameters correlated with age, time from injury, patient{\textquoteright}s outcome and white matter \{MRI\} hyperintensities. We found that whole-brain global approach restricted to single-fiber voxels showed significantly decreased fractional anisotropy (FA) (p = 0.002) and increased radial diffusivity (p = 0.011) in patients with mTBI compared with controls. The results restricted to single-fiber voxels were more significant and reproducible than those with the complete tract skeleton or the whole-brain tractography. \{FA\} correlated with patient outcomes, white matter hyperintensities and age. No correlation was observed between \{FA\} and time of scan post-injury. In conclusion, the global approach could be a promising imaging biomarker to detect white matter abnormalities following traumatic brain injury.}, keywords = {Diffusion-weighted magnetic resonance imaging, Global approach, Magnetic Resonance Imaging, probabilistic tractography, Traumatic brain injury}, issn = {2213-1582}, doi = {http://dx.doi.org/10.1016/j.nicl.2016.11.016}, url = {http://www.sciencedirect.com/science/article/pii/S2213158216302248}, author = {Mohammadian, Mehrbod and Timo Roine and Jussi Hirvonen and Timo Kurki and Henna Ala-Sepp{\"a}l{\"a} and Janek Frantz{\'e}n and Ari Katila and Anna Kyll{\"o}nen and Henna-Riikka Maanp{\"a}{\"a} and Jussi Posti and Riikka Takala and Jussi Tallus and Olli Tenovuo} } @article {1762, title = {Intrinsic connectivity reduces in vestibular-related regions after first-time exposure to short-term gravitational alterations}, journal = {Scientific Reports}, volume = {7}, year = {2017}, doi = {10.1038/s41598-017-03170-5}, author = {Angelique Van Ombergen and Floris L Wuyts and Ben Jeurissen and Jan Sijbers and Floris Vanhevel and Steven Jillings and Paul M Parizel and Stefan Sunaert and Paul H Van de Heyning and Vincent Dousset and Steven S L Laureys and Athena Demertzi} } @article {1775, title = {A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps}, journal = {Signal Image and Video Processing}, volume = {11}, year = {2017}, pages = { 913-920}, author = {P V Sudeep and Palanisamy, P and Chandrasekharan Kesavadas and Jan Sijbers and Arnold Jan den Dekker and Jeny Rajan} } @inproceedings {1808, title = {Pixel purity vertex component analysis}, booktitle = {IEEE IGARSS 2017, International Geoscience and Remote Sensing Symposium, Fort Worth, USA, July 23-28}, year = {2017}, author = {Rob Heylen and Mario Parente and Paul Scheunders} } @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 {1764, title = {Solving the Free Water Elimination Estimation Problem by Incorporating T2 Relaxation Properties}, year = {2017}, author = {Quinten Collier and Jelle Veraart and Arnold Jan den Dekker and Floris Vanhevel and Paul M Parizel and Jan Sijbers} } @article {1668, title = {Super-resolution T1 estimation: quantitative high resolution T1 mapping from a set of low resolution T1 weighted images with different slice orientations}, journal = {Magnetic Resonance in Medicine}, volume = {77}, year = {2017}, pages = {1818{\textendash}1830}, doi = {10.1002/mrm.26262}, author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Floris Vanhevel and Paul M Parizel and Jan Sijbers} } @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} } @inproceedings {1717, title = {Classification of hyperspectral images with very small training size using sparse unmixing}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, year = {2016}, address = {Beijing, China}, author = {Vera Andrejchenko and Rob Heylen and Paul Scheunders and Wilfried Philips and Wenzhi Liao} } @article {1584, title = {Cortical reorganization in an astronaut{\textquoteright}s brain after long-duration spaceflight}, journal = {Brain Structure and Function}, volume = {221}, year = {2016}, pages = {2873{\textendash}2876}, doi = {10.1007/s00429-015-1054-3}, author = {Athena Demertzi and Angelique Van Ombergen and Elena Tomilovskaya and Ben Jeurissen and Ekaterina V. Pechenkova and Carol Di Perri and Liudmila Litvinova and Enrico Amico and Alena Rumshiskaya and Ilya Rukavishnikov and Jan Sijbers and Valentin Sinitsyn and Inessa B. Kozlovskaya and Stefan Sunaert and Paul M Parizel and Paul H Van de Heyning and Steven S L Laureys and Floris L Wuyts} } @article {1651, title = {D-BRAIN: Anatomically Accurate Simulated Diffusion MRI Brain Data}, journal = {PlosOne}, volume = {11}, number = {3}, year = {2016}, pages = {1-23}, doi = {10.1371/journal.pone.0149778}, author = {Daniele Perrone and Ben Jeurissen and Jan Aelterman and Timo Roine and Jan Sijbers and Aleksandra Pizurica and Alexander Leemans and Wilfried Philips} } @article {1620, title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination}, journal = {NeuroImage}, volume = {125}, year = {2016}, pages = {363{\textendash}377}, doi = {10.1016/j.neuroimage.2015.10.052}, author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Maarten Naeyaert and Greetje Vanhoutte and Rafael Delgado Y Palacios and Jelle Praet and Els Fieremans and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye} } @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 {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} } @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 {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} } @inproceedings {1810, title = {Lidar information extraction by attribute filters with partial reconstruction}, booktitle = {IEEE IGARSS 2016, International Geoscience and Remote Sensing Symposium, pp. 1484-1487, Beijing, July 10-15 }, year = {2016}, doi = {10.1109/IGARSS.2016.7729379}, author = {Wenzhi Liao and M Della Mura and X Huang and Jocelyn Chanussot and S Gautama and Paul Scheunders and Wilfried Philips} } @conference {Roine2016-je, title = {Methodological Considerations on Graph Theoretical Analysis of Structural Brain Networks}, year = {2016}, pages = {3437}, author = {Roine, Timo and Ben Jeurissen and Perrone, Daniele and Jan Aelterman and Philips, Wilfried and Jan Sijbers and Leemans, Alexander} } @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-Marzán and van Blaaderen, Alfons and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf} } @mastersthesis {1713, title = {Super-resolution estimation of quantitative MRI parameters}, volume = {Doctor of Science}, year = {2016}, school = {University of Antwerp}, type = {PhD thesis}, author = {Gwendolyn Van Steenkiste} } @article {1536, title = {Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations}, journal = {Magnetic Resonance in Medicine}, volume = {75}, year = {2016}, pages = {181-195}, doi = {10.1002/mrm.25597}, url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.25597/abstract}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Jelle Veraart and Arnold Jan den Dekker and Paul M Parizel and Dirk H J Poot and Jan Sijbers} } @article {1541, title = {An accurate projection model for diffraction image formation and inversion using a polychromatic cone beam}, journal = {Journal of Applied Crystallography}, volume = {48}, year = {2015}, pages = {334-343}, author = {Wim Van Aarle and Ludwig, Wolfgang and King, Andrew and Dayakar Penumadu} } @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} } @conference {Van_Steenkiste2015-va, title = {Combination of super-resolution reconstruction diffusion tensor imaging and track density imaging reveals song control system connectivity in zebra finches}, year = {2015}, pages = {2861}, author = {Gwendolyn Van Steenkiste and Hamaide, Julie and Ben Jeurissen and Dirk H J Poot and Johan Van Audekerke and Jan Sijbers and Verhoye, Marleen} } @conference {1598, title = {Combination of super-resolution reconstruction diffusion tensor imaging and track density imaging reveals song control system connectivity in zebra finches}, volume = {23}, year = {2015}, pages = {2861}, author = {Gwendolyn Van Steenkiste and Hamaide, Julie and Ben Jeurissen and Dirk H J Poot and Johan Van Audekerke and Jan Sijbers and Marleen Verhoye} } @article {1604, title = {Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?}, journal = {Journal of Alzheimer{\textquoteright}s Disease}, volume = {48}, number = {4}, year = {2015}, pages = {937-948}, doi = {10.3233/JAD-150253}, author = {Hanna Struyfs and Wim Van Hecke and Jelle Veraart and Jan Sijbers and Sylvie Slaets and Maya De Belder and Laura Wuyts and Benjamin Peters and Kristel Sleegers and Caroline Robberecht and Van Broeckhoven, Christine and Frank De Belder and Paul M Parizel and Sebastiaan Engelborghs} } @conference {1594, title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination}, volume = {23}, number = {4332}, year = {2015}, author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Jelle Praet and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye} } @article {perrone2015effect, title = {The effect of Gibbs ringing artifacts on measures derived from diffusion MRI}, journal = {NeuroImage}, volume = {120}, year = {2015}, pages = {441{\textendash}455}, publisher = {Academic Press}, author = {Daniele Perrone and Jan Aelterman and Pi{\.z}urica, Aleksandra and Ben Jeurissen and Wilfried Philips and Alexander Leemans} } @article {1517, title = {Evaluation of an anthropometric shape model of the human scalp}, journal = {Applied Ergonomics}, volume = {48}, year = {2015}, pages = {70-85}, doi = {10.1016/j.apergo.2014.11.008}, author = {Daniel Lacko and Toon Huysmans and Paul M Parizel and Guido De Bruyne and Stijn Verwulgen and Marc M. Van Hulle and Jan Sijbers} } @article {1591, title = {Fast Neural Network Based X-Ray Tomography of Fruit on a Conveyor Belt}, journal = {Chemical Engineering Transactions}, volume = {44}, year = {2015}, pages = {181-186}, address = {Milano, Italy}, doi = {10.3303/CET1544031}, author = {Eline Janssens and Daan Pelt and Jan De Beenhouwer and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers} } @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 {Van_Ombergen2015-nk, title = {A first insight in regional brain changes after parabolic flight: a voxel-based morphometry study}, year = {2015}, pages = {1258}, author = {Angelique Van Ombergen and Ben Jeurissen and Floris Vanhevel and Loeckx, Dirk and Dousset, Vincent and Paul M Parizel and Floris L Wuyts} } @conference {1633, title = {High resolution diffusion tensor imaging in a clinically feasible scan time}, year = {2015}, doi = {10.3389/conf.fninf.2015.19.00016}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Steven Baete and Arnold Jan den Dekker and Dirk H J Poot and Fernando Boada and Jan Sijbers} } @inproceedings {1548, title = {High resolution T1 estimation from multiple low resolution magnetic resonance images}, booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI): From nano to macro}, volume = {12}, year = {2015}, pages = {1036-1039}, doi = {10.1109/ISBI.2015.7164048}, author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers} } @article {1519, title = {Informed constrained spherical deconvolution (iCSD)}, journal = {Medical Image Analysis}, volume = {24}, year = {2015}, pages = {269{\textendash}281}, type = {Original research}, chapter = {269}, abstract = {Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. However, the voxel sizes used in DW-MRI are relatively large, making DW-MRI prone to significant partial volume effects (PVE). These PVEs can be caused both by complex (e.g. crossing) WM fiber configurations and non-WM tissue, such as gray matter (GM) and cerebrospinal fluid. High angular resolution diffusion imaging methods have been developed to correctly characterize complex WM fiber configurations, but significant non-WM PVEs are also present in a large proportion of WM voxels. In constrained spherical deconvolution (CSD), the full fiber orientation distribution function (fODF) is deconvolved from clinically feasible DW data using a response function (RF) representing the signal of a single coherently oriented population of fibers. Non-WM PVEs cause a loss of precision in the detected fiber orientations and an emergence of false peaks in CSD, more prominently in voxels with GM PVEs. We propose a method, informed CSD (iCSD), to improve the estimation of fODFs under non-WM PVEs by modifying the RF to account for non-WM PVEs locally. In practice, the RF is modified based on tissue fractions estimated from high-resolution anatomical data. Results from simulation and in-vivo bootstrapping experiments demonstrate a significant improvement in the precision of the identified fiber orientations and in the number of false peaks detected under GM PVEs. Probabilistic whole brain tractography shows fiber density is increased in the major WM tracts and decreased in subcortical GM regions. The iCSD method significantly improves the fiber orientation estimation at the WM-GM interface, which is especially important in connectomics, where the connectivity between GM regions is analyzed.}, keywords = {Connectomics, constrained spherical deconvolution, Diffusion MRI, fiber orientation, gray matter, partial volume effect, Response function, Tractography}, doi = {10.1016/j.media.2015.01.001}, url = {http://www.sciencedirect.com/science/article/pii/S1361841515000080}, author = {Timo Roine and Ben Jeurissen and Daniele Perrone and Jan Aelterman and Wilfried Philips and Alexander Leemans and Jan Sijbers} } @article {roine2015isotropic, title = {Isotropic non-white matter partial volume effects in constrained spherical deconvolution}, journal = {Information-based methods for neuroimaging: analyzing structure, function and dynamics}, year = {2015}, pages = {112}, publisher = {Frontiers Media SA}, author = {Timo Roine and Ben Jeurissen and Daniele Perrone and Jan Aelterman and Alexander Leemans and Wilfried Philips and Jan Sijbers} } @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} } @conference {1561, title = {Partial discreteness: a new type of prior knowledge for MRI reconstruction}, volume = {23}, year = {2015}, pages = {3417}, author = {Gabriel Ramos-Llord{\'e}n and Segers, Hilde and Willem Jan Palenstijn and Arnold Jan den Dekker and Jan Sijbers} } @inproceedings {7351081, title = {Partially discrete magnetic resonance tomography}, booktitle = {2015 IEEE International Conference on Image Processing (ICIP)}, year = {2015}, month = {Sept}, pages = {1653-1657}, keywords = {Bayes methods, Bayesian segmentation, Bayesian segmentation regularization, biomedical MRI, Breast, breast implant MR images, computerised tomography, Discrete tomography, image reconstruction, image representation, image segmentation, Implants, medical image processing, MR angiography images, MR image reconstruction, MRI, partially discrete magnetic resonance tomography, reconstruction, Tomography, TV}, doi = {10.1109/ICIP.2015.7351081}, author = {Gabriel Ramos-Llord{\'e}n and Segers, Hilde and Willem Jan Palenstijn and Arnold Jan den Dekker and Jan Sijbers} } @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-Marzán and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf} } @inproceedings {2043, title = {SPIE ProceedingsEnergy calibration of photon counting detectors using x-ray tube potential as a reference for material decomposition applications}, booktitle = {SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging}, volume = {9412}, year = {2015}, pages = {941214}, publisher = {SPIE}, organization = {SPIE}, address = {Orlando, Florida, United States}, doi = {10.1117/12.2082979}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2082979}, author = {Das, Mini and Kandel, Bigyan and Park, Chan Soo and Zhihua Liang}, editor = {Hoeschen, Christoph and Kontos, Despina and Flohr, Thomas G.} } @conference {1520, title = {Super-resolution structural connectivity and anatomy of the zebra finch brain }, year = {2015}, author = {Gwendolyn Van Steenkiste and Hamaide, Julie and Ben Jeurissen and Dirk H J Poot and Johan Van Audekerke and Jan Sijbers and Marleen Verhoye} } @conference {1596, title = {Super-resolution T1 mapping: a simulation study}, volume = {23}, year = {2015}, pages = {1679}, author = {Gwendolyn Van Steenkiste and Dirk H J Poot and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers} } @inproceedings {1635, title = {Two-stage fusion of thermal hyperspectral and visible RGB image by PCA and guided filter}, booktitle = {IEEE Whispers 2015, Workshop on Hyperspectral Image and Signal Processing, June 2-5, Tokyo}, year = {2015}, author = {W. Liao and F. Huang and F. v. Coillie and Guy Thoonen and Aleksandra Pizurica and Paul Scheunders and Wilfried Philips} } @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} } @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} } @conference {roine2014ismrm, title = {Improving fiber orientation estimation in constrained spherical deconvolution under non-white matter partial volume effects}, year = {2014}, month = {05/2014}, pages = {4492}, author = {Timo Roine and Ben Jeurissen and Wilfried Philips and Alexander Leemans and Jan Sijbers} } @article {roine2014frontiers, title = {Isotropic non-white matter partial volume effects in constrained spherical deconvolution}, journal = {Frontiers in Neuroinformatics}, volume = {8}, number = {28}, year = {2014}, month = {03/2014}, pages = {1-9}, publisher = {Frontiers}, type = {Original Research}, abstract = {Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. Significant partial volume effects (PVE) are present in the DW signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM) and cerebrospinal fluid (CSF), and by multiple nonparallel WM fiber populations. High angular resolution diffusion imaging (HARDI) methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD). Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNR), fiber configurations, and tissue fractions. Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50 \% of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50 \% GM volume for maximum spherical harmonics orders of 8 and below, and already with 25 \% GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm2, reasonable SNR (~30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD. }, keywords = {constrained spherical deconvolution, Diffusion MRI, fiber orientation, gray matter, partial volume effect}, doi = {10.3389/fninf.2014.00028}, url = {http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00028/abstract}, author = {Timo Roine and Ben Jeurissen and Daniele Perrone and Jan Aelterman and Alexander Leemans and Wilfried Philips and Jan Sijbers} } @conference {1443, title = {Isotropic non-white matter partial volume effects in constrained spherical deconvolution}, year = {2014}, author = {Timo Roine and Ben Jeurissen and Wilfried Philips and Alexander Leemans and Jan Sijbers} } @conference {1559, title = {A Novel Method for Realistic DWI Data Generation}, volume = {22}, year = {2014}, pages = {4427}, address = {Milan, Italy}, author = {Daniele Perrone and Jan Aelterman and Ben Jeurissen and Aleksandra Pizurica and Wilfried Philips and Jan Sijbers} } @conference {1482, title = {Super-resolution reconstruction of diffusion parameters from multi-oriented diffusion weighted images}, year = {2014}, month = {january}, address = {Maastricht, The Netherlands}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Dirk H J Poot and Paul M Parizel and Jan Sijbers} } @conference {1483, title = {Super-resolution reconstruction of diffusion parameters from multi-oriented diffusion weighted images}, year = {2014}, month = {May}, address = {Milan, Italy}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Paul M Parizel and Dirk H J Poot 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} } @inproceedings {1478, title = {Type-2 fuzzy GMMs for robust text-independent speaker verification in noisy environments}, booktitle = {International Conference of Pattern Recognition}, year = {2014}, author = {Hector N. B. Pinheiro and Ing Ren Tsang and George D C Cavalcanti and Ing Jyh Tsang 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} } @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} } @article {1406, title = {Alveolar Nerve Unfolding Technique for Synoptic Analysis: Visualization and Quantification of Inferior Alveolar Nerve Tracings in Three-dimensional Cone-Beam Computed Tomography.}, journal = {The Journal of craniofacial surgery}, volume = {24}, year = {2013}, month = {2013 Jul}, pages = {e374-7}, abstract = {The aim of the technique presented here is to visualize the anatomical context of the inferior alveolar nerve (IAN) canal. For 2 cases, cone-beam computed tomography images of the mandible were obtained from patient files together with the manual preoperative IAN canal tracings. For both cases, similar to simulated panoramic images, a two-dimensional image is extracted from a three-dimensional cone-beam computed tomography image. Unlike panoramic images, the unfolding does not follow the general curvature of the mandible but follows the nerve tracing closely and places the traced nerve track on a horizontal central line. Because of the centering of the nerve tracing together with the nerve canal and its surroundings in a two-dimensional representation, the technique (ANUTSA [Alveolar Nerve Unfolding Technique for Synoptic Analysis]) allowed the first case to evidence the adjacency of root tips along the IAN, whereas in the second case the degree of penetration of the IAN by an implant is revealed. The global aspect of the representation through unfolding allowed for the detection of the anomalies and the IAN-penetrating lesion along the IAN canal at a glance.}, issn = {1536-3732}, doi = {10.1097/SCS.0b013e3182903013}, author = {Jacquet, Wolfgang and Nyssen, Edgard and Sun, Yi and De Munter, Stephanie and Jan Sijbers and Politis, Constantinus} } @conference {1433, title = {Analysis and modeling of isotropic partial volume effects in diffusion MRI}, volume = {7}, year = {2013}, month = {2013}, doi = {10.3389/conf.fninf.2013.10.00027}, author = {Timo Roine and Ben Jeurissen and Alexander Leemans and Wilfried Philips and Jan Sijbers} } @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 {1369, title = {Comprehensive framework for accurate diffusion MRI parameter estimation}, journal = {Magnetic Resonance in Medicine}, volume = {81}, year = {2013}, pages = {972-984}, doi = {10.1002/mrm.24529}, author = {Jelle Veraart and Jeny Rajan and Ron R Peeters and Alexander Leemans and Stefan Sunaert and Jan Sijbers} } @article {1377, title = {Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer{\textquoteright}s disease}, journal = {Magnetic Resonance in Medicine}, volume = {69}, year = {2013}, pages = {1115{\textendash}1121}, doi = {10.1002/mrm.24680}, author = {Greetje Vanhoutte and S. Pereson and Rafael Delgado Y Palacios and Pieter-Jan Guns and B. Asselbergh and Jelle Veraart and Jan Sijbers and Marleen Verhoye and Van Broeckhoven, Christine and Annemie Van Der Linden} } @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 {1361, title = {Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study.}, journal = {European radiology}, volume = {23}, year = {2013}, month = {2012 Jul 20}, pages = {57-64}, abstract = {OBJECTIVE: To evaluate the effect of monophasic combined oral contraceptive pill (COCP) and menstrual cycle phase in healthy young women on white matter (WM) organization using diffusion tensor imaging (DTI). METHODS: Thirty young women were included in the study; 15 women used COCP and 15 women had a natural cycle. All subjects underwent DTI magnetic resonance imaging during the follicular and luteal phase of their cycle, or in different COCP cycle phases. DTI parameters were obtained in different WM structures by performing diffusion tensor fibre tractography. Fractional anisotropy and mean diffusivity were calculated for different WM structures. Hormonal plasma concentrations were measured in peripheral venous blood samples and correlated with the DTI findings. RESULTS: We found a significant difference in mean diffusivity in the fornix between the COCP and the natural cycle group. Mean diffusivity values in the fornix were negatively correlated with luteinizing hormone and estradiol blood concentrations. CONCLUSION: An important part in the limbic system, the fornix, regulates emotional processes. Differences in diffusion parameters in the fornix may contribute to behavioural alternations related to COCP use. This finding also suggests that the use of oral contraceptives needs to be taken into account when designing DTI group studies. KEY POINTS: {\textbullet} Diffusion tensor MRI offers new insights into brain white matter microstructure. {\textbullet} The effects of oral hormonal contraception were examined in young women. {\textbullet} Diffusion tensor images and hormone blood concentrations were evaluated. {\textbullet} Women using hormonal contraception demonstrated higher mean diffusivity in the fornix. {\textbullet} These changes may contribute to behavioural alternations related to contraception use.}, issn = {1432-1084}, doi = {10.1007/s00330-012-2572-5}, author = {De Bondt, Timo and Wim Van Hecke and Jelle Veraart and Alexander Leemans and Jan Sijbers and Stefan Sunaert and Jacquemyn, Yves and Paul M Parizel} } @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 {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 {1413, title = {Reelin Associated With Restricted and Stereotyped Behavior Based on Principal Component Analysis on Autism Diagnostic Interview-Revised}, journal = {Autism - Open Access}, volume = {3}, year = {2013}, chapter = {107}, url = {http://www.omicsgroup.org/journals/2165-7890/2165-7890-3-107.pdf}, author = {Roine, Ulrika and Ripatti, Samuli and Rehnstr{\"o}m, Karola and Timo Roine and Kilpinen, Helena and Surakka, Ida and Wedenoja, Juho and Ylisaukko-oja, Tero and Kempas, Elli and Wessman, Jaana and Moilanen, Irma and Mattila, Marja-Leena and Kielinen, Marko and Jussila, Katja and Suomalainen, Saara and Pulkkinen, Esko and von Wendt, Lennart and Peltonen, Leena} } @article {1470, title = {Regional gray matter volume differences and sex-hormone correlations as a function of menstrual cycle phase and hormonal contraceptives use.}, journal = {Brain research}, volume = {1530}, year = {2013}, month = {2013 Sep 12}, pages = {22-31}, abstract = {During the menstrual cycle, hormone-driven functional and morphological changes occur in the female brain. The influence of hormonal contraceptives on these changes has received only little attention in the medical literature. The purpose of our study is to measure regional gray matter volume changes as a function of the cycle phase and use of hormonal contraceptives, in relation to blood concentrations of sex hormones. We performed a prospective study in 30 healthy young women; 15 women had a natural menstrual cycle and 15 were using monophasic combined hormonal contraceptives. MRI examinations were acquired at 2 specific time-points in the cycle (follicular and luteal phase). MRI studies included a T1-weighted, isotropic, high-resolution 3-D gradient echo acquisition, for the purpose of performing voxel based morphometry. Peripheral venous blood samples were obtained to determine concentrations of luteinizing hormone (LH), follicle stimulating hormone (FSH), estradiol, and progesterone. We found a highly significant negative correlation of regional gray matter volume in the anterior cingulate cortex with estradiol concentrations. To the best of our knowledge, this result has not been described before, and was only present in the natural cycle group, not in women using hormonal contraceptives. The anterior cingulate cortex is involved in emotion processing and there is literature describing behavioral alternations with changing hormone levels. Our findings provide a structural, morphological basis to support these data. Therefore, we advise neuroscientists to take into account the menstrual cycle phase and use of hormonal contraceptives, in order to avoid obtaining heterogeneous data sets, leading to a significant loss of accuracy and precision.}, issn = {1872-6240}, doi = {10.1016/j.brainres.2013.07.034}, author = {De Bondt, Timo and Jacquemyn, Y and Wim Van Hecke and Jan Sijbers and Stefan Sunaert and Paul M Parizel} } @article {1347, title = {Semi-supervised local discriminant analysis for feature extraction in hyperspectral images}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {51}, year = {2013}, pages = {184-198}, author = {W. Liao and Aleksandra Pizurica and Paul Scheunders and Wilfried Philips and Y Pi} } @conference {1385, title = {Super resolution reconstruction from differently oriented diffusion tensor data sets}, year = {2013}, month = {April}, pages = {3186}, address = {Salt Lake City, USA}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Jan Sijbers and Dirk H J Poot} } @conference {1384, title = {Super resolution reconstruction from differently oriented diffusion tensor data sets}, year = {2013}, month = {January}, address = {Rotterdam, The Netherlands}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Jan Sijbers and Dirk H J Poot} } @conference {1425, title = {Super resolution reconstruction of diffusion tensor parameters from multi-oriented diffusion weighted images}, year = {2013}, author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Dirk H J Poot and Jan Sijbers} } @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} } @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 {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} } @conference {1325, title = {Correction of Gibbs ringing in diffusion MRI data using total variation regularization}, year = {2012}, month = {January}, pages = {99}, keywords = {MRI distortion artefacts}, author = {Daniele Perrone and Jan Aelterman and Maryna Kudzinava and Jan Sijbers and Aleksandra Pizurica and Wilfried Philips and Alexander Leemans} } @article {1304, title = {Diffusion kurtosis imaging in the grading of gliomas}, journal = {Radiology}, volume = {2}, number = {263}, year = {2012}, pages = {492-501}, doi = {10.1148/radiol.12110927}, author = {Van Cauter, Sofie and Jelle Veraart and Jan Sijbers and Ron R Peeters and U. Himmelreich and S. Van Gool and Van Calenbergh, F. and De Vleeschouwer, S. and Wim Van Hecke and Stefan Sunaert} } @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} } @article {1313, title = {Force Feedback to Assist Active Contour Modelling for Tracheal Stenosis Segmentation}, journal = {Advances in Human-Computer Interaction}, volume = {2012}, year = {2012}, abstract = {Manual segmentation of structures for diagnosis and treatment of various diseases is a very time-consuming procedure. Therefore, some level of automation during the segmentation is desired, as it often significantly reduces the segmentation time. A typical solution is to allow manual interaction to steer the segmentation process, which is known as semiautomatic segmentation. In 2D, such interaction is usually achieved with click-and-drag operations, but in 3D a more sophisticated interface is called for. In this paper, we propose a semi-automatic Active Contour Modelling for the delineation of medical structures in 3D, tomographic images. Interaction is implemented with the employment of a 3D haptic device, which is used to steer the contour deformation towards the correct boundaries. In this way, valuable haptic feedback is provided about the 3D surface and its deformation. Experiments on simulated and real tracheal CT data showed that the proposed technique is an intuitive and effective segmentation mechanism.}, doi = {doi:10.1155/2012/632498}, url = {http://www.hindawi.com/journals/ahci/2012/632498/}, author = {Lode Vanacken and R{\^o}mulo Pinho and Jan Sijbers and Karen Coninx} } @conference {1714, title = {A framework for markerless alignment with full 3D flexibility}, year = {2012}, author = {Jan De Beenhouwer and Willem Jan Palenstijn and Folkert Bleichrodt and Kees Joost Batenburg and Jan Sijbers} } @article {1349, title = {Identification and characterization of Huntington related pathology: an in vivo DKI imaging study}, journal = {NeuroImage}, volume = {63}, year = {2012}, month = {09/2012}, pages = {653-662}, doi = {http://dx.doi.org/10.1016/j.neuroimage.2012.06.032}, author = {Ines Blockx and Marleen Verhoye and Johan Van Audekerke and Irene Bergwerf and Jack X Kane and Rafael Delgado Y Palacios and Jelle Veraart and Ben Jeurissen and Kerstin Raber and Von H{\"o}rsten, Stephan and Peter Ponsaerts and Jan Sijbers and Trygve B Leergaard and Annemie Van Der Linden} } @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} } @article {ThoonenMahmoodPeeterspscheund2012, title = {Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion}, journal = {Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of}, volume = {5}, number = {2}, year = {2012}, pages = {510 - 521}, abstract = {In this work, we treat the problem of combined classification of a high spatial resolution color image and a lower spatial resolution hyperspectral image of the same scene. The problem is particularly challenging, since we aim for classification maps at the spatial resolution of the color image. Contextual information is obtained from the color image by introducing Color Attribute Profiles (CAPs). Instead of treating the {\textquoteleft}R{\textquoteright}, {\textquoteleft}G{\textquoteright}, and {\textquoteleft}B{\textquoteright} bands separately, the color image is transformed into CIE-Lab space. In this color space, attribute profiles are extracted from the {\textquoteleft}L{\textquoteright} band, which corresponds to the Luminance, while the {\textquoteleft}a{\textquoteright} and {\textquoteleft}b{\textquoteright} bands, which contain the color information, are kept intact, and the resulting images are transformed back into RGB space. The spectral information is obtained from the hyperspectral image. A Composite Decision Fusion (CDF) strategy is proposed, combining a state-of-the-art kernel-based decision fusion technique with the popular composite kernel classification approach. Experiments are conducted, using simulated data and a real multisource dataset containing airborne hyperspectral data and orthophotographic data from a suburban area in Belgium. These experiments show that our CAPs perform well with respect to other approaches for extracting attribute profiles from high resolution color images, and that the proposed CDF strategy produces meaningful results with respect to concatenation and the highlighted state-of-the-art approaches for combining multisource data.}, keywords = {Color, image classification, morphological operations, multiresolution techniques, multisensor systems}, issn = {1939-1404}, doi = {10.1109/JSTARS.2011.2168317}, author = {Guy Thoonen and Zahid Mahmood and Stijn Peeters and Paul Scheunders} } @inproceedings {1299, title = {Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique}, booktitle = {SPIE Medical Imaging}, volume = {8313}, year = {2012}, month = {02/2012}, abstract = {Adaptive statistical iterative reconstruction (ASiR) is a new algorithm used in medical X-ray imaging. It combines the standard FBP and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. In this paper the effect of ASiR on the contrast to noise ratio (CNR) is studied using a low contrast phantom (Catphan). The experiments were done at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to FBP. For the same CNR the images from ASiR are obtained using 60\% less current, leading to a 60\% dose reduction.}, doi = {doi:10.1117/12.911283}, author = {Elke Van de Casteele and Paul M Parizel and Jan Sijbers} } @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} } @conference {1365, title = {Statistical shape modelling in support of user-centred BCI headset design}, year = {2012}, author = {Daniel Lacko and Toon Huysmans and Stijn Verwulgen and Paul M Parizel and Marc M. Van Hulle and Jan Sijbers} } @article {1393, title = {Through the Looking-Glass, and What the Quadratic Camera Found There}, journal = {The Mathematical Intelligencer}, volume = {34}, year = {2012}, month = {9/2012}, pages = {30 - 34}, issn = {0343-6993}, doi = {10.1007/s00283-012-9309-9}, author = {de Smit, Bart and McClure, Mark and Willem Jan Palenstijn and Sparling, E. Isaac and Wagon, Stan} } @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 {rpinhoTournoyjsijbers2011, title = {Assessment and Stenting of Tracheal Stenosis using Deformable Shape Models}, journal = {Medical Image Analysis}, volume = {15}, number = {2}, year = {2011}, pages = {250-266}, abstract = {This work presents a decision support system for the assessment of tracheal stenosis. In the proposed method, a statistical shape model of healthy tracheas is registered to a 3D CT image of a patient with tracheal stenosis. The registration yields an estimation of the shape of the patient{\textquoteright}s trachea as if stenosis was not present. From this point, the extent and the severity of the stenosis is assessed and stent parameters are obtained automatically. The method was extensively evaluated on simulation as well on real data and the results showed that it is accurate and fast enough to be used in the clinical setting.}, issn = {1361-8423}, doi = {http://dx.doi.org/doi:10.1016/j.media.2010.12.001}, author = {R{\^o}mulo Pinho and Kurt G. Tournoy and Jan Sijbers} } @inproceedings {WitteThoonenpscheundPizuricaPhilips2011, title = {Classification of multi-source images using color mathematical morphological profiles}, booktitle = {Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International}, year = {2011}, pages = {3919 - 3922}, address = {Vancouver, BC, Canada}, abstract = {In the remote sensing domain data from many different sources are often available. Each of these data sources are characterized by their own sensor- and platform-specific properties, i.e. spectral range, or spatial and spectral resolution. In this paper we consider a low spatial, but high spectral resolution satellite image, together with its high spatial resolution RGB color image, e.g. obtained by UAV. Spatial features are extracted from the color image by combining the three color bands R, G and B, ordering these color vectors, and presenting color mathematical morphological profiles accordingly. This way the spatial information contained in the correlation between the different bands is completely taken into account and thus also totally preserved in the feature extraction. In a classification experiment these color morphological profiles are combined with the spectral features of the hyperspectral image, and we show that the spatial characterization of the color image is improved.}, keywords = {Classification, Color, Morphological profiles, Multisource images, remote sensing}, isbn = {978-1-4577-1003-2}, issn = {2153-6996}, doi = {10.1109/IGARSS.2011.6050088}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=6050088\&isnumber=6048881}, author = {Val{\'e}rie De Witte and Guy Thoonen and Paul Scheunders and Aleksandra Pizurica and Wilfried Philips} } @inbook {1263, title = {Classification of Soft Tissue Tumors by Machine Learning Algorithms}, booktitle = {Soft Tissue Tumors}, year = {2011}, publisher = {InTech}, organization = {InTech}, issn = {978-953-307-862-5}, author = {Juntu, Jaber and Arthur M. De Schepper and Pieter Van Dyck and Dirk Van Dyck and Jan L Gielen and Paul M Parizel and Jan Sijbers} } @conference {jveraartwvheckedpootjsijbers2011, title = {Constrained maximum likelihood estimator for more accurate diffusion kurtosis tensor estimates}, year = {2011}, month = {January}, address = {Hoeven, The Netherlands}, author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Jan Sijbers} } @conference {Kudzinava_2011_WMSG, title = {Diffusion and kurtosis parameters in white matter of premature newborns}, year = {2011}, month = {August}, pages = {21}, address = {Reykjavik, Iceland}, abstract = {Diffusion Tensor Imaging (DTI) is often used to study brain maturation processes and white matter (WM) injuries in premature newborns. However, DTI assumes that water diffusion in biological tissues is free. In reality, there is always structural hindrance in WM, which only increases with age due to myelination. Diffusional Kurtosis Imaging (DKI) relaxes the assumption of free diffusion and allows estimation of conventional diffusion parameters plus new kurtosis measures, which are related to tissue complexity. In this work, we present and discuss the first statistics of DKI parameters in WM of two prematurely born infants.}, keywords = {anisotropy, diffusion, kurtosis, premature newborns, white matter}, author = {Maryna Kudzinava and A. Plaisier and J. Dudink and Jan Sijbers} } @conference {1307, title = {Distortion correction of DKI data: affine approach}, year = {2011}, month = {December}, abstract = {In this work, the performance of FMRIB{\textquoteright}s Linear Registration Tool (FLIRT) is evaluated with respect to motion and distortion correction of diffusion kurtosis imaging (DKI) data. FLIRT is tested on two DKI datasets heavily distorted by motion and eddy currents artefacts. Six different criteria are used for evaluation. Our results show that distortion correction using FLIRT substantially improves the original data. However, being an affine registration tool, FLIRT cannot cope with the amount of non-linear distortion present in DKI datasets. Hence, we conclude that, for correction of DKI data, non-linear registration techniques are more suitable.}, keywords = {medical imaging}, author = {Maryna Kudzinava and Alexander Leemans and Wilfried Philips and Daniele Perrone and Jan Aelterman and J. Dudink and Jan Sijbers} } @conference {1308, title = {Gibbs artifact suppression for DT-MRI data}, year = {2011}, month = {December}, keywords = {medical imaging}, author = {Daniele Perrone and Jan Aelterman and Maryna Kudzinava and Jan Sijbers and Aleksandra Pizurica and Wilfried Philips and Alexander Leemans} } @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 {S.jveraartjsijbersU.R.S.wvhecke2011, title = {Mean Kurtosis: a new potential biomarker for brain tumor grading}, year = {2011}, month = {January}, address = {Hoeven, The Netherlands}, author = {Van Cauter, Sofie and Jelle Veraart and Jan Sijbers and U. Himmelreich and Ron R Peeters and S. Van Gool and Wim Van Hecke} } @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} } @inproceedings {Kudzinava_2011_ISBI, title = {Optimized Workflow for Diffusion Kurtosis Imaging of Newborns}, booktitle = {ISBI, 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro}, year = {2011}, month = {April}, pages = {922-926}, address = {Chicago, USA}, abstract = {Diffusional kurtosis imaging (DKI) is a recently proposed extension of the conventional DTI model. It has been shown to offer more sensitive characterization of neural tissues than DTI. So far, DKI has only been applied to adult human and small animal studies, but not yet to human newborns. In this work, we present an optimized workflow for the acquisition and processing of DKI images of newborns. First, optimal set of diffusion weighting gradients for DKI studies of newborn subjects is proposed. Optimized gradients allow to estimate DKI parameters with the highest precision. Next, preprocessing and segmentation of the DKI data is considered, including motion correction, eddy currents suppression, intensity modulation and gradients reorientation. Finally, statistics of estimated diffusion and kurtosis parameters for different neonatal brain tissues are calculated.}, keywords = {diffusion and kurtosis parameters, DKI, motion correction, newborns, optimal gradients, precision}, doi = {10.1109/ISBI.2011.5872554}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=5872554}, author = {Maryna Kudzinava and Dirk H J Poot and A. Plaisier 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 {P.M.A.S.bjeurissJ.A.M.K.F.T.J.-F.C.2011, title = {Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom}, journal = {NeuroImage}, volume = {56}, number = {1}, year = {2011}, month = {May}, pages = {220-234}, author = {Pierre Fillard and Maxime Descoteaux and Alvina Goh and Sylvain Gouttard and Ben Jeurissen and James Malcolm and Alonso Ramirez-Manzanares and Marco Reisert and Ken Sakaie and Fatima Tensaouti and Ting-Shou Yo and Jean-Fran{\c c}ois Mangin and Cyril Poupon} } @article {1269, title = {Successive Cambia: A Developmental Oddity or an Adaptive Structure?}, journal = {PLoS ONE}, volume = {6}, year = {2011}, month = {1/2011}, pages = {e16558}, doi = {10.1371/journal.pone.0016558}, author = {Robert, Elisabeth M. R. and Schmitz, Nele and Boeren, Ilse and Driessens, Tess and Herremans, Kristof and Johan De Mey and Elke Van de Casteele and Beeckman, Hans and Koedam, Nico}, editor = {Peer, Wendy} } @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} } @article {wvheckeAleemanssdbackerBjeurisspmparizejsijbers2010, title = {Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study}, journal = {Human Brain Mapping}, volume = {31}, number = {1}, year = {2010}, pages = {98-114}, author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Ben Jeurissen and Paul M Parizel and Jan Sijbers} } @inbook {rpinhoTournoyjsijbers2010, title = {Computer-Aided Assessment and Stenting of Tracheal Stenosis}, booktitle = {Computer Aided Diagnosis of Lung Imaging}, year = {2010}, author = {R{\^o}mulo Pinho and Kurt G. Tournoy and Jan Sijbers}, editor = {Ayman El-Baz} } @article {wvheckeNagelsaleemansVandervlietjsijbersParizel2010, title = {Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis}, journal = {Journal of magnetic resonance imaging}, volume = {31}, number = {6}, year = {2010}, month = {May}, pages = {1492-1498}, author = {Wim Van Hecke and Guy Nagels and Alexander Leemans and Everhard Vandervliet and Jan Sijbers and Paul M Parizel} } @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} } @mastersthesis {1284, title = {A Decision Support System for the Assessment and Stenting of Tracheal Stenosis}, year = {2010}, month = {18/11/2010}, school = {University of Antwerp}, type = {PhD thesis}, address = {Antwerp}, abstract = {This thesis sets forth a decision support system that proposes a method for automatic assessment of tracheal stenosis and prediction of stent length and diameter from chest CT scans. The main idea behind the proposed method is to estimate the shape of the trachea of a patient as if stenosis were not present. This shape can be used the by the physician for surgery planning and is the basis for the automatic assessment of the stenosis and the prediction of patient-specific stents. }, author = {R{\^o}mulo Pinho} } @inproceedings {rpinhoTournoyGosselinjsijbers2010, title = {A Decision Support System for the Treatment of Tracheal Stenosis}, booktitle = {Proc. of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM)}, year = {2010}, month = {August}, pages = {72-76}, publisher = {IAPR}, organization = {IAPR}, address = {Istanbul}, author = {R{\^o}mulo Pinho and Kurt G. Tournoy and Robert Gosselin and Jan Sijbers} } @inproceedings {1319, title = {General and Efficient Super-Resolution method for Multi-Slice MRI}, booktitle = {Medical Image Computing and Computer Assisted Intervention}, volume = {13}, year = {2010}, pages = {615-622}, doi = {10.1007/978-3-642-15705-9_75}, author = {Dirk H J Poot and V. Van Meir and Jan Sijbers} } @article {dpootwpintjenmverhoyeavdlindejsijbers2010, title = {Improved B0 field map estimation for high field EPI}, journal = {Magnetic Resonance Imaging}, volume = {28}, number = {3}, year = {2010}, month = {April}, pages = {441-450}, author = {Dirk H J Poot and W. Pintjens and Marleen Verhoye and Annemie Van Der Linden and Jan Sijbers} } @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 {1189, title = {Noise measurement from magnitude MRI using local estimates of variance and skewness.}, journal = {Physics in medicine and biology}, volume = {55}, year = {2010}, month = {2010 Aug 21}, pages = {N441-9}, abstract = {In this note, we address the estimation of the noise level in magnitude magnetic resonance (MR) images in the absence of background data. Most of the methods proposed earlier exploit the Rayleigh distributed background region in MR images to estimate the noise level. These methods, however, cannot be used for images where no background information is available. In this note, we propose two different approaches for noise level estimation in the absence of the image background. The first method is based on the local estimation of the noise variance using maximum likelihood estimation and the second method is based on the local estimation of the skewness of the magnitude data distribution. Experimental results on synthetic and real MR image datasets show that the proposed estimators accurately estimate the noise level in a magnitude MR image, even without background data.}, keywords = {Algorithms, Artifacts, Brain, Data Interpretation, Statistical, Fourier Analysis, Humans, Image Processing, Computer-Assisted, Likelihood Functions, Magnetic Resonance Imaging, Models, Statistical, Myocardium, Normal Distribution, Reproducibility of Results}, issn = {1361-6560}, doi = {10.1088/0031-9155/55/16/N02}, author = {Jeny Rajan and Dirk H J Poot and Juntu, Jaber and Jan Sijbers} } @article {dpootajdendekAchtenmverhoyejsijbers2010, title = {Optimal experimental design for Diffusion Kurtosis Imaging}, journal = {IEEE Transactions on Medical Imaging}, volume = {29}, number = {3}, year = {2010}, pages = {819-829}, doi = {http://dx.doi.org/10.1109/TMI.2009.2037915}, author = {Dirk H J Poot and Arnold Jan den Dekker and Eric Achten and Marleen Verhoye and Jan Sijbers} } @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} } @inproceedings {DBLP:conf/iciar/RajanPJS10, title = {Segmentation Based Noise Variance Estimation from Background MRI Data}, booktitle = {ICIAR }, volume = {6111}, year = {2010}, month = {2010}, pages = {62-70}, publisher = {Springer LNCS}, organization = {Springer LNCS}, address = {Porto, Portugal}, author = {Jeny Rajan and Dirk H J Poot and Juntu, Jaber and Jan Sijbers} } @article {1268, title = {X-ray micro tomography and image analysis as complementary methods for morphological characterization and coating thickness measurement of coated particles}, journal = {Advanced Powder Technology}, volume = {21}, year = {2010}, month = {11/2010}, pages = {663 - 675}, issn = {09218831}, doi = {10.1016/j.apt.2010.08.002}, author = {Perfetti, Giacomo and Elke Van de Casteele and Rieger, Bernd and Wildeboer, Willem J. and Meesters, Gabrie M.H.} } @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} } @mastersthesis {1290, title = {Advances in the reconstruction and statistical processing of Magnetic Resonance images}, volume = {PhD in Sciences: Physics}, year = {2009}, type = {PhD Thesis}, author = {Dirk H J Poot} } @inproceedings {rpinhoTournoyGosselinjsijbers2009, title = {Assessment of Tracheal Stenosis Using Active Shape Models of Healthy Tracheas: A Surface Registration Study}, booktitle = {Proceedings of 2nd International Workshop on Pulmonary Image Analysis}, year = {2009}, month = {September}, pages = {125-136}, author = {R{\^o}mulo Pinho and Kurt G. Tournoy and Robert Gosselin and Jan Sijbers} } @article {wvheckejsijberssdbackerdpootParizelaleemans2009, title = {On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods}, journal = {NeuroImage}, volume = {46}, number = {3}, year = {2009}, month = {July}, pages = {692-707}, doi = {10.1016/j.neuroimage.2008.07.006}, author = {Wim Van Hecke and Jan Sijbers and Steve De Backer and Dirk H J Poot and Paul M Parizel and Alexander Leemans} } @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 {1376, title = {A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions.}, journal = {Journal of magnetic resonance imaging : JMRI}, volume = {30}, year = {2009}, month = {2009 Jul}, pages = {25-34}, abstract = {PURPOSE: To examine the T(2)-normal appearing spinal cord of patients with multiple sclerosis (MS) using diffusion tensor imaging. MATERIALS AND METHODS: Diffusion tensor images of the spinal cord were acquired from 21 healthy subjects, 11 MS patients with spinal cord lesions, and 10 MS patients without spinal cord lesions on the T(2)-weighted MR images. Different diffusion measures were evaluated using both a region of interest (ROI) -based and a diffusion tensor tractography-based segmentation approach. RESULTS: It was observed that the FA, the transverse diffusivity lambda(perpendicular), and the ratio of the longitudinal and transverse diffusivities (lambda(parallel)/lambda (perpendicular)) were significantly lower in the spinal cord of MS patients with spinal cord lesions compared with the control subjects using both the ROI method (P = 0.014, P = 0.028, and P = 0.039, respectively) and the tractography-based approach (P = 0.006, P = 0.037, and P = 0.012, respectively). For both image analysis methods, the FA and the lambda (parallel)/lambda (perpendicular) values were significantly different between the control group and the MS patient group without T(2) spinal cord lesions (P = 0.013). CONCLUSION: Our results suggest that the spinal cord may still be affected by MS, even when lesions are not detected on a conventional MR scan. In addition, we demonstrated that diffusion tensor tractography is a robust tool to analyze the spinal cord of MS patients.}, keywords = {Adult, Analysis of Variance, anisotropy, Diffusion Magnetic Resonance Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Multiple Sclerosis, Observer Variation, Reproducibility of Results, Spinal Cord, Spinal Cord Diseases, Thoracic Vertebrae}, issn = {1053-1807}, doi = {10.1002/jmri.21817}, author = {Wim Van Hecke and Guy Nagels and Emonds, Griet and Alexander Leemans and Jan Sijbers and van Goethem, Johan and Paul M Parizel} } @conference {PalaciosmverhoyeAudekerkedpootjsijbersWiborgavdlinde2009, title = {DKI visualizes hippocampal alterations in the chronic mild stress ratmodel}, volume = {2009}, year = {2009}, month = {April}, pages = {744}, author = {Rafael Delgado Y Palacios and Marleen Verhoye and Johan Van Audekerke and Dirk H J Poot and Jan Sijbers and O. Wiborg and Annemie Van Der Linden} } @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 {PostnovSchutterjsijbersKarperienClerck2009, title = {Glucocorticoid-Induced Osteoporosis in Growing Mice Is Not Prevented by Simultaneous Intermittent PTH Treatment}, journal = {Calcified Tissue International}, volume = {85}, number = {6}, year = {2009}, month = {December}, pages = {530-537}, doi = {10.1007/s00223-009-9301-3}, author = {A. Postnov and T. De Schutter and Jan Sijbers and M. Karperien and N. De Clerck} } @mastersthesis {1271, title = {Improved Processing for Diffusion Tensor Magnetic Resonance Images for Coregistration, Atlas Construction, and Voxel Based Analysis}, year = {2009}, school = {University of Antwerp}, type = {PhD thesis}, address = {Antwerp}, author = {Wim Van Hecke} } @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} } @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} } @conference {dpootajdendekjsijbers2009, title = {Pearson Set of Distributions as Improved Signal Model for Diffusion Kurtosis Imaging}, year = {2009}, month = {April}, pages = {1383}, publisher = {ISMRM}, author = {Dirk H J Poot and Arnold Jan den Dekker and Jan Sijbers} } @article {1374, title = {Quantitative diffusion tensor imaging in amyotrophic lateral sclerosis: revisited.}, journal = {Human brain mapping}, volume = {30}, year = {2009}, month = {2009 Nov}, pages = {3657-75}, abstract = {Voxel-based analyses (VBA) are increasingly being used to detect white matter abnormalities with diffusion tensor imaging (DTI) in different types of pathologies. However, the validity, specificity, and sensitivity of statistical inferences of group differences to a large extent depend on the quality of the spatial normalization of the DTI images. Using high-dimensional nonrigid coregistration techniques that are able to align both the spatial and orientational diffusion information and incorporate appropriate templates that contain this complete DT information may improve this quality. Alternatively, a hybrid technique such as tract-based spatial statistics (TBSS) may improve the reliability of the statistical results by generating voxel-wise statistics without the need for perfect image alignment and spatial smoothing. In this study, we have used (1) a coregistration algorithm that was optimized for coregistration of DTI data and (2) a population-based DTI atlas to reanalyze our previously published VBA, which compared the fractional anisotropy and mean diffusivity maps of patients with amyotrophic lateral sclerosis (ALS) with those of healthy controls. Additionally, we performed a complementary TBSS analysis to improve our understanding and interpretation of the VBA results. We demonstrate that, as the overall variance of the diffusion properties is lowered after normalizing the DTI data with such recently developed techniques (VBA using our own optimized high-dimensional nonrigid coregistration and TBSS), more reliable voxel-wise statistical results can be obtained than had previously been possible, with our VBA and TBSS yielding very similar results. This study provides support for the view of ALS as a multisystem disease, in which the entire frontotemporal lobe is implicated.}, keywords = {Adult, Aged, Algorithms, Amyotrophic Lateral Sclerosis, anisotropy, Brain, Brain Mapping, Case-Control Studies, diffusion tensor imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Reproducibility of Results, Sensitivity and Specificity, Statistics as Topic}, issn = {1097-0193}, doi = {10.1002/hbm.20794}, author = {Caroline A Sage and Wim Van Hecke and Ron R Peeters and Jan Sijbers and Robberecht, Wim and Paul M Parizel and Marchal, Guy and Alexander Leemans and Stefan Sunaert} } @inproceedings {rpinhoLuyckxjsijbers2009, title = {Robust Region Growing Based Intrathoracic Airway Tree Segmentation}, booktitle = {Proceedings of 2nd International Workshop on Pulmonary Image Analysis}, year = {2009}, month = {September}, pages = {261-271}, author = {R{\^o}mulo Pinho and Sten Luyckx and Jan Sijbers} } @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 {wvheckealeemanssdbackerParizeljsijbers2008, title = {On the construction of a ground truth methodology to evaluate VBM analysis results of diffusion tensor images}, booktitle = {European Society for Magnetic Resonance in Medicine and Biology}, year = {2008}, month = {October}, address = {Valencia, Spain}, author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Paul M Parizel and Jan Sijbers} } @article {wvheckejsijbersDagostinoMaessdbackerVandervlietParizelaleemans2008, title = {On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain}, journal = {NeuroImage}, volume = {43}, number = {1}, year = {2008}, pages = {69-80}, doi = {0.1016/j.neuroimage.2008.07.006}, author = {Wim Van Hecke and Jan Sijbers and E. Dagostino and F. Maes and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Alexander Leemans} } @article {sdbackerPizuricaHuysmansPhilipspscheund2008, title = {Denoising of Multicomponent Images Using Wavelet Least-Squares Estimators}, journal = {Image and Vision Computing}, volume = {26}, number = {7}, year = {2008}, month = {July}, pages = {1038-1051}, author = {Steve De Backer and Aleksandra Pizurica and B. Huysmans and Wilfried Philips and Paul Scheunders} } @inproceedings {wvheckejsijbersGoethemParizel2008, title = {Diffusion tensor tractography reveals white matter alterations in the normal appearing spinal cord of Multiple Sclerosis patients}, booktitle = {European Society for Magnetic Resonance in Medicine and Biology}, year = {2008}, month = {October}, address = {Valencia, Spain}, author = {Wim Van Hecke and Jan Sijbers and J. Van Goethem and Paul M Parizel} } @inproceedings {wvheckealeemansAgostinosdbackerVandervlietParizeljsijbers2008, title = {The evaluation of a population based diffusion tensor image atlas using a ground truth method}, booktitle = {Proceedings of SPIE Medical Imaging}, volume = {6914}, year = {2008}, month = {February}, address = {San Diego, USA}, author = {Wim Van Hecke and Alexander Leemans and E. Dagostino and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers} } @inproceedings {dpootjsijbersajdendek2008, title = {An exploration of spatial similarities in temporal noise spectra in fMRI measurements}, booktitle = {Proceedings of SPIE Medical Imaging 2008}, volume = {6914}, year = {2008}, month = {February}, pages = {69142}, address = {San Diego, CA, USA}, author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @conference {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} } @conference {wvheckealeemanssdbackerVandervlietjsijberspmparize2008, title = {A Ground Truth Analysis of the Preservation of Diffusion Tensor Information in a Population Specific Atlas}, year = {2008}, month = {May}, address = {Toronto, Canada}, author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Jan Sijbers and Paul M Parizel} } @conference {wpintjendpootmverhoyeavdlindejsijbers2008, title = {Improved EPI Correction: Upgrading An Ultrafast Imaging Technique}, year = {2008}, month = {March}, author = {W. Pintjens and Dirk H J Poot and Marleen Verhoye and Annemie Van Der Linden and Jan Sijbers} } @inproceedings {dpootjsijbersajdendek2008, title = {Optimizing the Diffusion Kurtosis imaging acquisition}, booktitle = {European Society for Magnetic Resonance in Medicine and Biology}, year = {2008}, month = {October}, address = {Valencia, Spain}, author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker} } @inproceedings {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 {Thoonen08, title = {Spatial Classification of Hyperspectral Data of Dune Vegetation along the Belgian Coast}, booktitle = {Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International}, volume = {3}, year = {2008}, month = {July}, pages = {III-483 - III-486}, address = {Boston, MA, USA}, abstract = {This work evaluates a classification method, including spatial information, for dune vegetation along the Belgian coastline. The used method is a recursive supervised segmentation algorithm based on a tree-structured Markov Random Field. This technique describes a K-ary field as a sequence of binary Markov Random Fields, each of which is represented by a node in the tree. The obtained classification results were compared to results with the same data set, for a purely spectral classification and a spectral classification, followed by spatial smoothing.}, keywords = {airborne data, airborne radar, Belgian Coast, binary Markov Random Field, dune environment, dune vegetation mapping, Europe, hyperspectral data, image classification, image segmentation, Markov processes, spatial classification, spatial smoothing, supervised segmentation algorithm, tree-structured Markov Random Field, trees (mathematics), TS-MRF model, vegetation mapping}, isbn = {978-1-4244-2807-6}, doi = {10.1109/IGARSS.2008.4779389}, author = {Guy Thoonen and Steve De Backer and S. Provoost and Pieter Kempeneers and Paul Scheunders} } @inproceedings {wpintjendpootmverhoyeavdlindejsijbers2008, title = {Susceptibility correction for improved tractography using high field DT-EPI}, booktitle = {Proceedings of SPIE Medical Imaging}, volume = {6914}, year = {2008}, month = {February}, address = {San Diego, USA}, author = {W. Pintjens and Dirk H J Poot and Marleen Verhoye and Annemie Van Der Linden and Jan Sijbers} } @inproceedings {rpinhothuysmanVosjsijbers2008, title = {Tracheal Stent Prediction Using Statistical Deformable Models of Healthy Tracheas}, booktitle = {Liege Image Days 2008: Medical Imaging}, year = {2008}, month = {March}, author = {R{\^o}mulo Pinho and Toon Huysmans and W. Vos and Jan Sijbers} } @inproceedings {rpinhothuysmanVosjsijbers2008, title = {Tracheal Stent Prediction Using Statistical Deformable Models of Tubular Shapes}, booktitle = {Proceedings of SPIE Medical Imaging}, year = {2008}, month = {February}, publisher = {SPIE}, organization = {SPIE}, address = {San Diego, CA, USA}, doi = {http://dx.doi.org/10.1117/12.770237}, author = {R{\^o}mulo Pinho and Toon Huysmans and W. Vos and Jan Sijbers} } @article {wvheckealeemansjsijbersVandervlietGoethemParizel2008, title = {A tracking based DTI segmentation method for the detection of diffusion-related changes of the cervical spinal cord with aging}, journal = {Journal of Magnetic Resonance Imaging}, volume = {27}, number = {5}, year = {2008}, month = {March}, pages = {978-991}, doi = {10.1002/jmri.21338}, author = {Wim Van Hecke and Alexander Leemans and Jan Sijbers and Everhard Vandervliet and J. Van Goethem and Paul M Parizel} } @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} } @article {jsijbersdpootajdendekwpintjen2007, title = {Automatic estimation of the noise variance from the histogram of a magnetic resonance image}, journal = {Physics in Medicine and Biology}, volume = {52}, number = {5}, year = {2007}, month = {February}, pages = {1335-1348}, doi = {10.1088/0031-9155/52/5/009}, author = {Jan Sijbers and Dirk H J Poot and Arnold Jan den Dekker and W. Pintjens} } @inproceedings {pscheundsdbackerPizuricaHuysmansPhilips2007, title = {Bayesian Wavelet-based Denoising of Multicomponent Images}, booktitle = {Proceedings Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, 9-12 september, Vol. 6763-OK (12 pages)}, year = {2007}, author = {Paul Scheunders and Steve De Backer and Aleksandra Pizurica and B. Huysmans and Wilfried Philips} } @inproceedings {wvheckeDagostinoaleemansParizelMaesjsijbers2007, title = {On the construction of a healthy brain inter-subject diffusion tensor image and tractography atlas}, booktitle = {32nd Congress of the Europea Society of NeuroRadiolog}, year = {2007}, pages = {146}, author = {Wim Van Hecke and E. Dagostino and Alexander Leemans and Paul M Parizel and F. Maes and Jan Sijbers} } @inproceedings {wvheckealeemansBrabanderLaridonClaeysCeulemansGoethemParizeljsijbers2007, title = {Diffusion Tensor Fiber Tracking Reveals Probst Bundles in Patients with Agenesis of the Corpus Callosum}, booktitle = {32nd Congress of the Europea Society of NeuroRadiolog}, year = {2007}, pages = {135}, author = {Wim Van Hecke and Alexander Leemans and N. De Brabander and A. Laridon and K. Claeys and B. Ceulemans and J. Van Goethem and Paul M Parizel and Jan Sijbers} } @inproceedings {Parizelwvhecke2007, title = {Diffusion Tensor Imaging: Is it really useful?}, booktitle = {32nd Congress of the Europea Society of NeuroRadiolog}, year = {2007}, author = {Paul M Parizel and Wim Van Hecke} } @inproceedings {wvheckealeemansjsijbersParizelGoethem2007, title = {Diffusion Tensor Tractoghraphy Reaveals Spinal Cord Alterations in Patients with Multiple Sclerosis}, booktitle = {32nd Congress of the Europea Society of NeuroRadiolog}, year = {2007}, pages = {129}, author = {Wim Van Hecke and Alexander Leemans and Jan Sijbers and Paul M Parizel and J. Van Goethem} } @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 {ParizelRompaeyLoockwvheckeGoethemaleemansjsijbers2007, title = {Influence of User-Defined Parameters on Diffusion Tensor Tractography of the Corticospinal Tract}, journal = {The Neuroradiology Journal}, number = {20}, year = {2007}, pages = {139-147}, author = {Paul M Parizel and V. Van Rompaey and R. Van Loock and Wim Van Hecke and J. Van Goethem and Alexander Leemans and Jan Sijbers} } @article {wvheckealeemansD{\textquoteright}AgostinosdbackerVandervlietParizeljsijbers2007, title = {Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information}, journal = {IEEE Transactions on Medical Imaging}, volume = {26}, number = {11}, year = {2007}, pages = {1598-1612}, author = {Wim Van Hecke and Alexander Leemans and E. Dagostino and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers} } @inproceedings {wvheckealeemansVandervlietParizeljsijbers2007, title = {An optimized tensor orientation strategy for non-rigid alignment of DT-MRI data}, booktitle = {Joint Annual Meeting ISMRM-ESMRMB}, year = {2007}, address = {Berlin}, author = {Wim Van Hecke and Alexander Leemans and Everhard Vandervliet and Paul M Parizel and Jan Sijbers} } @inproceedings {rpinhojsijbersthuysman2007, title = {Segmentation of The Human Trachea Using Deformable Statistical Models of Tubular Shapes}, booktitle = {Proceedings of Advanced Concepts for Intelligent Vision Systems}, series = {Lecture Notes in Computer Science}, volume = {4678}, year = {2007}, month = {August}, pages = {531-542}, doi = {http://dx.doi.org/10.1007/978-3-540-74607-2_48}, author = {R{\^o}mulo Pinho and Jan Sijbers and Toon Huysmans} } @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 {dpootjsijbersDekkerwpintjen2006, title = {Automatic estimation of the noise variance from the histogram of a magnetic resonance image}, booktitle = {IEEE/EBMS Benelux Symposium proceedings}, year = {2006}, month = {December}, pages = {135-138}, publisher = {IEEE/EMBS}, organization = {IEEE/EMBS}, author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker and W. Pintjens} } @inproceedings {VandervlietNagelsHeineckewvheckealeemansjsijbersParizel2006, title = {On the cause and mechanisms of the negative BOLD response in fMRI}, booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {308}, address = {Warsaw, Poland}, author = {Everhard Vandervliet and Guy Nagels and A. Heinecke and Wim Van Hecke and Alexander Leemans and Jan Sijbers and Paul M Parizel} } @inproceedings {wpintjenjsijbersmverhoyeAudekerkeavdlinde2006, title = {A Combined Correction Scheme For EPI Distortions at 7 Tesla}, booktitle = {Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium}, year = {2006}, pages = {147-150}, address = {Brussels, Belgium}, author = {W. Pintjens and Jan Sijbers and Marleen Verhoye and Johan Van Audekerke and Annemie Van Der Linden} } @inproceedings {wvheckealeemansjsijbersParizelGoethem2006, title = {A comparison of diffusion tensor analysis methods for detecting age-related changes of the normal appearing spinal cord}, booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {293-294}, address = {Warsaw, Poland}, author = {Wim Van Hecke and Alexander Leemans and Jan Sijbers and Paul M Parizel and J. Van Goethem} } @inproceedings {wvheckealeemansBrabanderLaridonCeulemansJParizel2006, title = {Diffusion tensor fiber tracking in patients with agenesis of the corpus callosum}, booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {34-35}, address = {Warsaw, Poland}, author = {Wim Van Hecke and Alexander Leemans and N. De Brabander and A. Laridon and B. Ceulemans and Jan Sijbers and Paul M Parizel} } @inproceedings {wvheckealeemansjsijbersParizelGoethem2006, title = {DTI of normal appearing spinal cord in elderly}, booktitle = {44th Annual Meeting of the American Society of Neuroradiology}, year = {2006}, month = {May}, pages = {380-381}, address = {San Diego, USA}, author = {Wim Van Hecke and Alexander Leemans and Jan Sijbers and Paul M Parizel and J. Van Goethem} } @inproceedings {rpinhojsijbersVos2006, title = {Efficient approaches to intrathoracic airway tree segmentations}, booktitle = {Proceedings of the Biomedical Engineering IEEE/EMBS Benelux Symposium}, volume = {2}, year = {2006}, month = {December}, pages = {151-154}, address = {Brussels, Belgium}, author = {R{\^o}mulo Pinho and Jan Sijbers and W. Vos} } @inproceedings {dpootjsijbersajdendekBos2006, title = {Estimation of the noise variance from the background histogram mode of an MR image}, booktitle = {Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium)}, year = {2006}, month = {March}, pages = {159-162}, address = {Antwerp, Belgium}, author = {Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker and R. Bos} } @inproceedings {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 {NagelsVandervlietwvheckeEngelborghshoogheCrasParizelDeyn2006, title = {fMRI during PASAT and PVSAT in mild MS, moderate MS and normal volunteers.}, booktitle = {22nd Congress of the European Committee for}, year = {2006}, address = {Madrid, Spain}, author = {Guy Nagels and Everhard Vandervliet and Wim Van Hecke and Sebastiaan Engelborghs and M.B. D hooghe and P. Cras and Paul M Parizel and P.P. De Deyn} } @inproceedings {wvheckealeemanssdbackerVandervlietParizelAgostinojsijbers2006, title = {Multi-channel coregistration of diffusion tensor images based on a viscous fluid model}, booktitle = {Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium}, year = {2006}, pages = {139-142}, address = {Brussels, Belgium}, author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Paul M Parizel and E. Dagostino and Jan Sijbers} } @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 {aleemansjsijberssdbackerVandervlietParizel2006, title = {Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data}, booktitle = {14th Scientific Meeting - International Society for Magnetic Resonance in Medicine}, year = {2006}, pages = {437}, address = {Seattle, USA}, author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel} } @article {aleemansjsijberssdbackerVandervlietParizel2006, title = {Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data}, journal = {Magnetic Resonance in Medicine}, volume = {55}, number = {6}, year = {2006}, pages = {1414-1423}, author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel} } @inproceedings {wvheckealeemanssdbackerVandervlietParizeljsijbersAgostino2006, title = {Non-rigid coregistration of diffusion tensor images using a viscous fluid model.}, booktitle = {23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {191-192}, address = {Warsaw, Poland}, author = {Wim Van Hecke and Alexander Leemans and Steve De Backer and Everhard Vandervliet and Paul M Parizel and Jan Sijbers and E. Dagostino} } @inproceedings {wvheckealeemansjsijbersParizelGoethem2006, title = {A preliminary study of diffusion tensor imaging and tractography of the spinal cord in elderly}, booktitle = {21th Annual Symposium - Belgian Hospital Physicists Association}, year = {2006}, pages = {61}, address = {Ghent, Belgium}, author = {Wim Van Hecke and Alexander Leemans and Jan Sijbers and Paul M Parizel and J. Van Goethem} } @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 {wpintjenjsijbersmverhoyeAudekerkeLinden2006, title = {A total correction scheme for EPI distortions at high field}, booktitle = {22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology}, year = {2006}, pages = {328-329}, address = {Warsaw, Poland}, author = {W. Pintjens and Jan Sijbers and Marleen Verhoye and Johan Van Audekerke and Annemie Van Der Linden} } @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} } @article {aleemansjsijberssdbackerVandervlietParizel2005, title = {Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information}, journal = {Lecture Notes in Computer Science}, volume = {3708}, year = {2005}, pages = {523-530}, author = {Alexander Leemans and Jan Sijbers and Steve De Backer and Everhard Vandervliet and Paul M Parizel} } @inproceedings {jjuntujsijbersdvandyckGielen2005, title = {Bias Field Correction for MRI Images}, booktitle = {Proceedings of the 4th International Conference on Computer Recognition Systems (CORES05)}, series = {Advances in Computer Science}, year = {2005}, month = {May}, pages = {543-551}, publisher = {Springer}, organization = {Springer}, address = {Rydzyna Castle, Poland}, author = {Juntu, Jaber and Jan Sijbers and Dirk Van Dyck and Jan L Gielen}, editor = {Marek Kurzynsji and Edward Puchala and Michal Wozniak and Andrzej Zolnierek} } @article {ParizelGoethemHauweSalgadoVandervlietaleemans2005, title = {Characterization of brain tumors}, journal = {NeuroRadiology}, volume = {47}, year = {2005}, pages = {80-83}, author = {Paul M Parizel and J. Van Goethem and L. van den Hauwe and R. Salgado and Everhard Vandervliet and Alexander Leemans} } @inproceedings {aleemanssdbackerjsijbersVandervlietParizel2005, title = {End point clustering for diffusion tensor white matter fiber bundle tractography}, booktitle = {22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology}, year = {2005}, pages = {129-130}, address = {Basle, Switzerland}, author = {Alexander Leemans and Steve De Backer and Jan Sijbers and Everhard Vandervliet and Paul M Parizel} } @inproceedings {aleemansjsijbersParizel2005, title = {A Graphical Toolbox for Exploratory Diffusion Tensor Imaging and Fiber Tractography}, booktitle = {14th Annual Meeting - Section for Magnetic Resonance Technologists}, year = {2005}, address = {Miami, USA}, author = {Alexander Leemans and Jan Sijbers and Paul M Parizel} } @inproceedings {KempeneerssdbackerDebruynProvoostpscheund2005, title = {Hyperspectral classification applied to the Belgian coastline}, booktitle = {SPIE Remote Sensing, Bruges, Belgium, 19-22 september}, volume = {5982}, number = {15}, year = {2005}, author = {Pieter Kempeneers and Steve De Backer and W. Debruyn and S. Provoost and Paul Scheunders} } @inproceedings {KempeneersSterckxDebruynParkRuddicksdbackerpscheund2005, title = {Retrieval of oceanic constituents from ocean color using simulated annealing}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, 25-29 July}, volume = {8}, year = {2005}, pages = {5651-5654}, author = {Pieter Kempeneers and S Sterckx and W. Debruyn and Y. Park and K. Ruddick and Steve De Backer and Paul Scheunders} } @inproceedings {aleemanssdbackerjsijbersVandervlietParizel2005, title = {TRACT: Tissue Relative Anisotropy based Curvature Thresholding for deterministic MR diffusion tensor tractography}, booktitle = {22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology}, year = {2005}, pages = {289}, address = {Basle, Switzerland}, author = {Alexander Leemans and Steve De Backer and Jan Sijbers and Everhard Vandervliet and Paul M Parizel} } @inproceedings {PizuricaHuysmanspscheundPhilips2005, title = {Wavelet domain denoising of multispectral remote sensing imagery adapted to the local spatial and spectral context}, booktitle = {IEEE International Geoscience and Remote Sensing Symp. IGARSS 2005, Seoul, Korea, 25-29 July}, volume = {6}, year = {2005}, pages = {4260-4263}, address = {Seoul, Korea}, author = {Aleksandra Pizurica and B. Huysmans and Paul Scheunders and Wilfried Philips} } @inproceedings {PizuricaPhilipspscheund2005, title = {Wavelet domain denoising of single-band and multi-band images adapted to the probability of the presence of features of interes}, booktitle = {SPIE Wavelets XI, San Diego, California, USA, 31 July {\textendash} 4 Aug}, volume = {5914}, year = {2005}, pages = {508-521}, author = {Aleksandra Pizurica and Wilfried Philips and Paul Scheunders} } @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 {PizuricapscheundPhilips2004, title = {Multiresolution multispectral image denoising based on probability of presence of features of interest}, booktitle = {Advanced Concepts in Image and Vision Systems, Brussels}, year = {2004}, pages = {357-364}, author = {Aleksandra Pizurica and Paul Scheunders and Wilfried Philips} } @inproceedings {jsijbersPostnov2004, title = {Reduction of ring artifacts in high resolution micro-CT images}, booktitle = {Advanced Concepts for Intelligent Vision Systems (ACIVS)}, year = {2004}, month = {September}, address = {Brussels, Belgium}, author = {Jan Sijbers and A. Postnov} } @article {jsijbersPostnov2004, title = {Reduction of ring artifacts in high resolution micro-CT reconstructions}, journal = {Physics in Medicine and Biology}, volume = {49}, number = {14}, year = {2004}, pages = {247-253}, doi = {doi:10.1088/0031-9155/49/14/N06}, author = {Jan Sijbers and A. Postnov} } @article {HungpscheundPhamSuColeman2004, title = {Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification}, journal = {International Journal of Fuzzy Systems}, volume = {6}, number = {3}, year = {2004}, pages = {107-117}, author = {C.C. Hung and Paul Scheunders and M. Pham and M.C. Su and T. Coleman} } @inproceedings {mverhoyeMichielsjsijbersEelenPeetersAudekerkeDHoogheDeynavdlinde2000, title = {Changes during pentetrazol-induced epilepsy in rat recorded by simultaneous EEG/MRI at 7T}, booktitle = {SPIE Medical Imaging}, volume = {3978}, year = {2000}, month = {February}, pages = {485-493}, address = {San Diego, USA}, author = {Marleen Verhoye and I. Michiels and Jan Sijbers and J. Eelen and Ron R Peeters and Johan Van Audekerke and R. Dhooghe and P.P. De Deyn and Annemie Van Der Linden}, editor = {Chin-Tu Chen, Anne V. Clough} } @inproceedings {mverhoyeCampPeetersjsijbersAudekerkeavdlinde2000, title = {On-line simultaneous BOLD/EEG measurements of functional activity during pentylenetetrazol induced epilepsy in the rat}, booktitle = {16th annual meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB00)}, year = {2000}, month = {September}, address = {Paris, France}, author = {Marleen Verhoye and N. Van Camp and Ron R Peeters and Jan Sijbers and Johan Van Audekerke and Annemie Van Der Linden} } @inproceedings {VanhouttemverhoyePeetersjsijbersEelenDHoogheDeynavdlinde2000, title = {Simultaneously recording of EEG/fMRI to study neurophysiological changes in rat brain during pentetrazol induced epileptic seizures}, booktitle = {Federation of European Neuroscience (FENS) Millennium Meeting}, volume = {12}, year = {2000}, month = {June}, pages = {107}, address = {Brighton, UK}, author = {Greetje Vanhoutte and Marleen Verhoye and Ron R Peeters and Jan Sijbers and J. Eelen and R. Dhooghe and P.P. De Deyn and Annemie Van Der Linden} } @article {AudekerkemverhoyePeetersjsijbersavdlinde2000, title = {Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous MRI and EEG acquisition at 7T}, journal = {Magnetic Resonance Imaging}, volume = {18}, number = {7}, year = {2000}, pages = {887-891}, doi = {https://doi.org/10.1016/S0730-725X(00)00172-7}, author = {Johan Van Audekerke and Marleen Verhoye and Ron R Peeters and Jan Sijbers and Annemie Van Der Linden} } @inproceedings {AudekerkejsijbersMichielsmverhoyePeetersavdlinde1999, title = {Novel design of an RF-antenna with integrated EEG electrodes for combined EEG and fMRI in animals}, booktitle = {16th annual meeting: Magnetic Resonance Materials in Physics, Biology, and Medicine}, year = {1999}, month = {September}, address = {Sevilla, Spain}, author = {Johan Van Audekerke and Jan Sijbers and I. Michiels and Marleen Verhoye and Ron R Peeters and Annemie Van Der Linden} }