Publications

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Journal Article
J. Rajan, Jeurissen, B., Verhoye, M., Van Audekerke, J., and Sijbers, J., “Maximum likelihood estimation based denoising of magnetic resonance images using restricted local neighborhoods”, Physics in Medicine and Biology, vol. 56, pp. 5221-5234, 2011.PDF icon Download full paper (643.93 KB)
J. Sijbers, den Dekker, A. J., Scheunders, P., and Van Dyck, D., “Maximum Likelihood estimation of Rician distribution parameters”, IEEE Transactions on Medical Imaging, vol. 17, pp. 357-361, 1998.PDF icon Download paper (106.26 KB)
J. Sijbers and den Dekker, A. J., “Maximum Likelihood estimation of signal amplitude and noise variance from MR data”, Magnetic Resonance in Medicine, vol. 51, pp. 586-594, 2004.PDF icon Download full paper (295.12 KB)
B. Goris, De Beenhouwer, J., De Backer, A., Zanaga, D., Batenburg, K. J., Sánchez-Iglesias, A., Liz-Marzán, L. M., Van Aert, S., Bals, S., Sijbers, J., and Van Tendeloo, G., “Measuring Lattice Strain in Three Dimensions through Electron Microscopy”, Nano Letters, vol. 15, no. 10, pp. 6996–7001, 2015.
J. Gao, Liang, Z., Soper, D. E., Lai, H. - L., Nadolsky, P. M., and Yuan, C. - P., “MEKS: A program for computation of inclusive jet cross sections at hadron colliders”, Computer Physics Communications, vol. 184, no. 6, pp. 1626 - 1642, 2013.
W. Van den Broek, Rosenauer, A., Sijbers, J., Van Dyck, D., and Van Aert, S., “A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM Ultramicroscopy”, Ultramicroscopy, vol. 141, pp. 22–31, 2014.
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.
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.
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., “MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, no. 5522815, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.57 MB)
B. Rast, Koirala, B., Scheunders, P., and Chanussot, J., “MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon ieee_journal_misicnet.pdf (11.02 MB)
P. Kempeneers, Zarco-Tejada, P. J., North, P. R. J., De Backer, S., Delalieux, S., Sepulcre-Canto, G., Morales, F., van Aardt, J., Sagardoy, R., Coppin, P., and Scheunders, P., “Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery”, International Journal of Remote Sensing, vol. 29, pp. 5093-5111, 2008.
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)
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)
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)
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)
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.
H. Aerts, Schirner, M., Jeurissen, B., Van Roost, D., Achten, E., Ritter, P., and Marinazzo, D., “Modeling brain dynamics in brain tumor patients using The Virtual Brain”, eNeuro, 2018.
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. 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)
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.
S. De Backer, Cornelissen, F., Lemeire, J., Nuydens, R., Meert, T., Schelkens, P., and Scheunders, P., “Mosiacing of Fibered Fluorescence Microscopy Video”, Lecture notes in Computer Science, vol. 5259, pp. 915-923, 2008.
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.
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.
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Gloaguen, R., and Scheunders, P., “MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6518-6530, 2022.PDF icon ms2a-net_multiscale_spectralspatial_association_network_for_hyperspectral_image_clustering.pdf (12.33 MB)
A. Duijster, De Backer, S., and Scheunders, P., “Multicomponent image restoration, an experimental study”, Lecture Notes in Computer Science, vol. 4633, pp. 58-68, 2007.

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