Publications

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Patent
K. J. Batenburg, Sijbers, J., and Plantagie, L., “Filter for Tomographic Reconstructions”, U.S. Patent WO2013011031A12014.
K. J. Batenburg and Sijbers, J., “Dynamic tomography angle selection”, U.S. Patent PCT/EP2012/0714212013.
J. Cant and Sijbers, J., “Computerized Tomographic Image Exposure and Reconstruction Method”, U.S. Patent PCT/EP2015/0599562016.PDF icon Download patent (595.32 KB)
M. Van Dael, Verboven, P., Nicolai, B., Dhaene, J., Van Hoorebeke, L., and Sijbers, J., “Automated quality control and selection ”, U.S. Patent PCT/EP2016/0557182016.
Miscellaneous
G. Ramos-Llordén, den Dekker, A. J., and Sijbers, J., “Joint motion correction and estimation for T1 mapping: proof of concept”, Medical Imaging Summer School 2014, Favignana, Italy. 2014.
Journal Article
J. Sanctorum, De Beenhouwer, J., and Sijbers, J., “X-ray phase contrast simulation for grating-based interferometry using GATE”, Optics Express, vol. 28, no. 22, pp. 33390-33412, 2020.PDF icon Download paper (2.5 MB)
B. Huyge, Renders, J., Sanctorum, J., De Beenhouwer, J., and Sijbers, J., “X-ray image reconstruction for continuous acquisitions with a generalized motion model”, Optics Express, In Press.
H. Zivari Adab, Chalavi, S., Beets, I., Gooijers, J., Leunissen, I., Cheval, B., Collier, Q., Sijbers, J., Jeurissen, B., Swinnen, S. P., and Boisgontier, M., “White matter microstructural organization of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults”, European Journal of Neuroscience , vol. 47, no. 5, pp. 446–459, 2018.
J. Veraart, Sijbers, J., Sunaert, S., Leemans, A., and Jeurissen, B., “Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls.”, NeuroImage, vol. 81, no. 1, pp. 335-346, 2013.PDF icon Download paper (2.89 MB)
J. Sijbers, Verhoye, M., Scheunders, P., Van Der Linden, A., Van Dyck, D., and Raman, E., “Watershed based segmentation of 3D MR data for volume quantization”, Magnetic Resonance Imaging, vol. 15, pp. 679-688, 1997.PDF icon Download paper (3.18 MB)
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, In Press.
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.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)
P. Lopes, Van Herck, P., Verhoelst, E., Wirix-Speetjens, R., Sijbers, J., Bosmans, J., and Vander Sloten, J., “Using particle systems for mitral valve segmentation from 3D transoesophageal echocardiography (3D TOE) - a proof of concept”, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 11, no. 1, pp. 112-120, 2023.
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “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 of Neurotrauma, vol. 40, no. 13-14, pp. 1317-1338, 2023.
M. Bührer, Xu, H., Eller, J., Sijbers, J., Stampanoni, M., and Marone, F., “Unveiling Water Dynamics in Fuel Cells from Time-Resolved Tomographic Microscopy Data”, Scientific Reports, vol. 10, no. 16388 , 2020.PDF icon Download paper (4.12 MB)
W. S. Oliveira, Teixeira, J. V., Tsang, I. R., Cavalcanti, G. D. C., and Sijbers, J., “Unsupervised Retinal Vessel Segmentation Using Combined Filters”, Plos One, vol. 11, pp. 1-21, 2016.
G. Ramos-Llordén, den Dekker, A. J., Van Steenkiste, G., Jeurissen, B., Vanhevel, F., Van Audekerke, J., Verhoye, M., and Sijbers, J., “A unified Maximum Likelihood framework for simultaneous motion and T1 estimation in quantitative MR T1 mapping”, IEEE Transactions on Medical Imaging, vol. 36, no. 2, pp. 433 - 446, 2017.
W. Van Hecke, Leemans, A., Sijbers, J., Vandervliet, E., Van Goethem, J., and Parizel, P. M., “A tracking based DTI segmentation method for the detection of diffusion-related changes of the cervical spinal cord with aging”, Journal of Magnetic Resonance Imaging, vol. 27, pp. 978-991, 2008.PDF icon Download paper (4.4 MB)
D. Van Dyck, Bettens, E., Sijbers, J., Op de Beeck, M., van den Bos, A., den Dekker, A. J., Jansen, J., and Zandbergen, H., “Towards quantitative structure determination through electron holographic methods”, Materials Characterization, vol. 42, pp. 265-281, 1999.PDF icon Download paper (6.71 MB)
Z. Liang, Van Heteren, A., Sijbers, J., and De Beenhouwer, J., “Toward denoising of 3D CT scans with few data”, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.PDF icon Download paper (5.93 MB)
F. De Carlo, Gursoy, D., Ching, D., Batenburg, K. J., Ludwig, W., Mancini, L., Welford, F. M., Mokso, R., Pelt, D., Sijbers, J., and Rivers, M., “TomoBank: A Tomographic Data Repository for Computational X-ray Science”, Measurement Science and Technology, vol. 29, no. 3, pp. 1-10, 2018.PDF icon Download paper (5.71 MB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging”, Frontiers in Neuroscience, pp. 1-18, 2022.PDF icon Download paper (5.96 MB)
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., “To Recurse or not to Recurse A Low Dose CT Study”, Progress in Artificial Intelligence, vol. 10, pp. 65–81, 2021.
K. Stanković, Booth, B. G., Danckaers, F., Burg, F., Vermaelen, P., Duerinck, S., Sijbers, J., and Huysmans, T., “Three-dimensional quantitative analysis of healthy foot shape: a proof of concept study”, Journal of Foot and Ankle Research, vol. 11, no. 8, pp. 1-13, 2018.PDF icon Download paper (2.24 MB)

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