Publications

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2019
H. Verhelst, Giraldo, D., Linden, C. Vander, Vingerhoets, G., Jeurissen, B., and Caeyenberghs, K., Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis., Neurorehabil Neural Repair, p. 1545968319868720, 2019.
M. Van Dael, Verboven, P., Zanella, A., Sijbers, J., and Nicolai, B., Combination of shape and X-ray inspection for apple internal quality control: in silico analysis of the methodology based on X-ray computed tomography, Postharvest Biology and Technology, vol. 148, pp. 218-227, 2019.
V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields, Remote Sensing, vol. 11, 2019.
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., Diffusion MRI fiber tractography of the brain, NMR in Biomedicine, 2019.
E. Byl, Bladt, P., Lebeer, S., and Kiekens, F., Importance of pressure plasticity during compression of probiotic tablet formulations, European Journal of Pharmaceutics and Biopharmaceutics, 2019.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling, Computers in Biology and Medicine, vol. 105, pp. 27-38, 2019.
J. Fatermans, Van Aert, S., and den Dekker, A. J., The maximum a posteriori probability rule for atom column detection from HAADF STEM images, Ultramicroscopy, vol. 201, pp. 81-91, 2019.
J. Sanctorum, Adriaens, D., Dirckx, J. J. J., Sijbers, J., Van Ginneken, C., Aerts, P., and Van Wassenbergh, S., Methods for characterization and optimisation of measuring performance of stereoscopic x-ray systems with image intensifiers, Measurement Science and Technology, vol. 30, no. 10, 2019.
J. - D. Tournier, Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C. - H., and Connelly, A., MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation., Neuroimage, p. 116137, 2019.
R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., Nonlinear hyperspectral unmixing with graphical models, IEEE Transaction on Geoscience and Remote Sensing, 2019.
M. Naeyaert, Roose, D., Mai, Z., Keliris, A. J., Sijbers, J., Van Der Linden, A., and Verhoye, M., Normalized Averaged Range (nAR), a Robust Quantification Method for MPIO-content, Journal of Magnetic Resonance, vol. 300, pp. 18-27, 2019.
N. Six, De Beenhouwer, J., and Sijbers, J., poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT, Optics Express, vol. 27, no. 23, pp. 33427-33435, 2019.PDF icon Download paper (997.08 KB)
F. Danckaers, Huysmans, T., Hallemans, A., De Bruyne, G., Truijen, S., and Sijbers, J., Posture normalization of 3D body scans, Ergonomics, vol. 62, no. 6, 2019.PDF icon Download paper (5.03 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Sijbers, J., and Leemans, A., Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks, Medical Image Analysis, vol. 52, pp. 56-67, 2019.PDF icon Download paper (4.03 MB)
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., A supervised method for nonlinear hyperspectral unmixing, Remote Sensing, vol. 11, no. 20 , 2019.
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.
S. Van Dongen, Danckaers, F., Beerten, J., and Huysmans, T., Women's preferences for male facial masculinity are not condition-dependent in a large online study, The All Results Journals: Biol, vol. 10, no. 1, 2019.
2018
K. J. Batenburg, De Carlo, F., Mancini, L., and Sijbers, J., Advanced X-ray tomography: experiment, modeling, and algorithms, Measurement Science and Technology, vol. 29, no. 8, p. 080101, 2018.
A. Van Ombergen, Jillings, S., Jeurissen, B., Tomilovskaya, E., Rühl, M., Rumshiskaya, A., Nosikova, I., Litvinova, L., Annen, J., Pechenkova, E. V., Kozlovskaya, I. B., Sunaert, S., Parizel, P. M., Sinitsyn, V., Laureys, S. S. L., Sijbers, J., Eulenburg, Pzu, and Wuyts, F. L., Brain Tissue–Volume Changes in Cosmonauts, New England Journal of Medicine, vol. 379, no. 17, pp. 1678 - 1680, 2018.
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform, ISPRS Journal of Photogrammetry and Remote Sensing , vol. 138, pp. 121-138, 2018.
J. Praet, Manyakov, N., Muchene, L., Mai, Z., Terzopoulos, V., De Backer, S., Torremans, A., Guns, P. - J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D., Schmidt, M., Van Der Linden, A., and Verhoye, M., Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology., Alzheimer's Research & Therapy , vol. 10, no. 1, pp. 1-16, 2018.
Q. Collier, Veraart, J., Jeurissen, B., Vanhevel, F., Pullens, P., Parizel, P. M., den Dekker, A. J., and Sijbers, J., Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach, Magnetic Resonance in Medicine, vol. 80, no. 2, pp. 802-813, 2018.PDF icon Download paper (1.93 MB)
E. Van de Casteele, Perilli, E., Van Aarle, W., Reynolds, K., and Sijbers, J., Discrete tomography in an in vivo small animal bone study, Journal of Bone and Mineral Metabolism, vol. 36, no. 1, pp. 40–53, 2018.
J. Goyens, Vasilopoulou-Kampitsi, M., Claes, R., Sijbers, J., and Mancini, L., Enhanced contrast in X-ray microtomographic images of the membranous labyrinth using different X-ray sources and scanning modes, Journal of Anatomy, vol. 233, p. 770--782, 2018.PDF icon Download paper (1.44 MB)
W. Keustermans, Huysmans, T., Danckaers, F., Zarowski, A., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., High quality statistical shape modelling of the human nasal cavity and applications, Royal Society Open Science, vol. 5, no. 12, 2018.PDF icon Download paper (1.85 MB)

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