Publications

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Journal Article
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., “Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.”, Magnetic resonance imaging, vol. 30, no. 10, pp. 1512-8, 2012.
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., “Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images”, Magnetic Resonance Imaging, vol. 30, no. 10, pp. 1512-1518, 2012.PDF icon Download full paper (1.11 MB)
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., “Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning”, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., “Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning”, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 2021.
J. Rajan, Poot, D. H. J., Juntu, J., and Sijbers, J., “Noise measurement from magnitude MRI using local estimates of variance and skewness.”, Physics in medicine and biology, vol. 55, no. 16, pp. N441-9, 2010.PDF icon Download paper (219.85 KB)
J. Rajan, den Dekker, A. J., and Sijbers, J., “A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test”, Signal Processing, vol. 103, pp. 16-23, 2014.
H. K. Jenssen, Oberlander, B. C., De Beenhouwer, J., Sijbers, J., and Verwerft, M., “Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor”, Progress in Nuclear Energy, vol. 72, pp. 55-62, 2014.
R. F. Kooy, Reyniers, E., Verhoye, M., Sijbers, J., Cras, P., Oostra, B. A., Willems, P. J., and Van Der Linden, A., “Neuroanatomy of the fragile X knockout mouse brain studied using in vivo high resolution Magnetic Resonance Imaging (MRI)”, European Journal of Human Genetics, vol. 7, pp. 526-532, 1999.PDF icon ejhg99.pdf (261.08 KB)
E. Janssens, De Beenhouwer, J., Van Dael, M., De Schryver, T., Van Hoorebeke, L., Verboven, P., Nicolai, B., and Sijbers, J., “Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection”, Measurement Science and Technology, vol. 29, no. 3, 2018.PDF icon Download paper (3.4 MB)
B. Jeurissen, Tournier, J. - D., Dhollander, T., Connelly, A., and Sijbers, J., “Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data”, NeuroImage, vol. 103, pp. 411–426, 2014.
M. Van Dael, Verboven, P., Dhaene, J., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., “Multisensor X-ray inspection of internal defects in horticultural products”, Postharvest Biology and Technology, vol. 128, pp. 33–43, 2017.
A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., “Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data”, Magnetic Resonance in Medicine, vol. 55, pp. 1414-1423, 2006.
A. Dabravolski, Batenburg, K. J., and Sijbers, J., “A Multiresolution Approach to Discrete Tomography Using DART”, PLoS ONE, vol. 9, no. 9, 2014.PDF icon Download paper (6.13 MB)
S. Cools, Ghysels, P., Van Aarle, W., Sijbers, J., and Vanroose, W., “A multi-level preconditioned Krylov method for the efficient solution of algebraic tomographic reconstruction problems”, Journal of Computational and Applied Mathematics, vol. 238, no. 1, pp. 1-16, 2015.
V. Van Nieuwenhove, De Beenhouwer, J., Vlassenbroeck, J., Brennan, M., and Sijbers, J., “MoVIT: A tomographic reconstruction framework for 4D-CT”, Optics Express, vol. 25, no. 16, pp. 19236-19250, 2017.
N. Van Camp, Vreys, R., Van Laere, K., Lauwers, E., Beque, D., Verhoye, M., Casteels, C., Verbruggen, A., Debyser, Z., Mortelmans, L., Sijbers, J., Nuyts, J., Baekelandt, V., and Van Der Linden, A., “Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson's disease discerned with microSPECT and quantitative MRI.”, Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 23, no. 2, pp. 65-75, 2010.
J. Veraart, Poot, D. H. J., Van Hecke, W., Blockx, I., Van Der Linden, A., Verhoye, M., and Sijbers, J., “More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging”, Magnetic Resonance in Medicine, vol. 65, pp. 138-145, 2011.PDF icon Download paper (387.31 KB)
E. Nazemi, Six, N., Iuso, D., De Samber, B., Sijbers, J., and De Beenhouwer, J., “Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction”, Applied Sciences, vol. 11, no. 7, 2021.PDF icon Download paper (4.96 MB)
J. Cant, Palenstijn, W. J., Behiels, G., and Sijbers, J., “Modeling blurring effects due to continuous gantry rotation: application to region of interest tomography”, Medical Physics, vol. 42, no. 5, pp. 2709-2717, 2015.
E. Bettens, Van Dyck, D., den Dekker, A. J., Sijbers, J., and van den Bos, A., “Model-based two-object resolution from observations having counting statistics”, Ultramicroscopy, vol. 77, pp. 37-48, 1999.PDF icon Download full paper (226 KB)
Q. Beirinckx, Jeurissen, B., Nicastro, M., Poot, D. H. J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping”, Computerized Medical Imaging and Graphics, vol. 100, no. 102071, pp. 1-16, 2022.PDF icon Download paper (15.42 MB)PDF icon Download supplementary material (1.35 MB)
Q. Beirinckx, Bladt, P., van der Plas, M. C. E., van Osch, M. J. P., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Model-based super-resolution reconstruction for pseudo-continuous Arterial Spin Labeling”, NeuroImage, vol. 286, p. 120506, 2024.PDF icon Download paper (7.23 MB)PDF icon Download supplementary material (20.75 MB)
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “A model-based correction method for beam hardening artefacts in X-ray microtomography”, Journal of X-ray science and technology, vol. 12, pp. 53-57, 2004.PDF icon Download full paper (632.04 KB)
I. Blockx, De Groof, G., Verhoye, M., Van Audekerke, J., Raber, K., Poot, D. H. J., Sijbers, J., Osmand, A. P., Von Hörsten, S., and Van Der Linden, A., “Microstructural changes observed with DKI in a transgenic Huntington rat model: Evidence for abnormal neurodevelopment.”, NeuroImage, vol. 59, pp. 957-67, 2012.
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.

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