Publications

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Journal Article
L. F. Alves Pereira, Janssens, E., Cavalcanti, G. D. C., Tsang, I. R., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Inline Discrete Tomography system: application to agricultural product inspection, Computers and Electronics in Agriculture, vol. 138, pp. 117–126, 2017.
T. B. A. de Carvalho, Sibaldo, M. A., Tsang, I. J., Cavalcanti, G. D. C., Sijbers, J., and Tsang, I. R., IntensityPatches and RegionPatches for Image Recognition, Applied Soft Computing, vol. 62, pp. 176-186, 2018.
T. B. A. de Carvalho, Sibaldo, M. A., Tsang, I. J., Cavalcanti, G. D. C., Sijbers, J., and Tsang, I. R., IntensityPatches and RegionPatches for Image Recognition, Applied Soft Computing, vol. 62, pp. 176-186, 2018.
S. Bugani, Camaiti, M., Morselli, L., Van de Casteele, E., and Janssens, K., Investigating morphological changes in treated vs. untreated stone building materials by x-ray micro-CT, Analytical and Bioanalytical Chemistry, vol. 391, no. 4, pp. 1343 - 1350, 2008.
S. Bugani, Camaiti, M., Morselli, L., Van de Casteele, E., and Janssens, K., Investigation on porosity changes of Lecce stone due to conservation treatments by means of x-ray nano- and improved micro-computed tomography: preliminary results, X-Ray Spectrometry, vol. 36, no. 5, pp. 316 - 320, 2007.
Q. Collier, Veraart, J., Jeurissen, B., den Dekker, A. J., and Sijbers, J., Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters, Magnetic Resonance in Medicine, vol. 73, no. 6, pp. 2174–2184, 2015.
L. Emsell, Leemans, A., Langan, C., Van Hecke, W., Barker, G. J., McCarthy, P., Jeurissen, B., Sijbers, J., Sunaert, S., Cannon, D. M., and McDonald, C., Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study, Biologicial Psychiatry, vol. 73, no. 2, pp. 194-201, 2013.
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.
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.
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.
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.
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.
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.
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.
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)
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., Noise reduction in hyperspectral imagery: overview and application, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
J. Kenney, McInerney, S., McPhilemy, G., Najt, P., Scanlon, C., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Donohoe, G., Hallahan, B., McDonald, C., and Cannon, D., P. 3.033 Lateralisation of the arcuate fasciculus in psychosis & the role in verbal learning & auditory verbal hallucinations, European Neuropsychopharmacology, vol. 26, no. 1, pp. S76–S77, 2016.
G. Van Eyndhoven, Kurttepeli, M., Van Oers, C. J., Cool, P., Bals, S., Batenburg, K. J., and Sijbers, J., Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials, Ultramicroscopy, vol. 148, pp. 10-19, 2015.
M. Roshani, Phan, G., Faraj, R. Hassan, Phan, N. - H., Roshani, G. Hossein, Corniani, E., and Nazemi, E., Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products, Nuclear Engineering and Technology, 2020.PDF icon 1-s2.0-s1738573320308779-main.pdf (1.38 MB)
E. Ribeiro Sabidussi, Klein, S., Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., Recurrent Inference Machines as inverse problem solvers for MR relaxometry, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
A. Cuyt, Sijbers, J., Verdonk, B., and Van Dyck, D., Region and Contour Identification of Physical Objects, Applied Numerical Analysis Computational Mathematics, vol. 1, pp. 343-352, 2004.
F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.

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