Publications

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Journal Article
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. 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.
S. Verwulgen, Lacko, D., Vleugels, J., Vaes, K., Danckaers, F., De Bruyne, G., and Huysmans, T., A new data structure and workflow for using 3D anthropometry in the design of wearable products, International Journal of Industrial Ergonomics, vol. 64, pp. 108 - 117, 2018.
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)
P. Scheunders, A multivalued image wavelet representation based on multiscale fundamental forms, IEEE Transactions on Image Processing, vol. 11, pp. 568-575, 2002.
B. Jeurissen and Szczepankiewicz, F., Multi-tissue spherical deconvolution of tensor-valued diffusion MRI., Neuroimage, vol. 245, p. 118717, 2021.
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.
G. Thoonen, Mahmood, Z., Peeters, S., and Scheunders, P., Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, vol. 5, pp. 510 - 521, 2012.
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.
B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Lorenz, S., Fuchs, M., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures, IEEE Sensors Journal, 2023.PDF icon a_multisensor_hyperspectral_benchmark_dataset_for_unmixing_of_intimate_mixtures_1_.pdf (22.13 MB)
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)
R. Heylen and Scheunders, P., A multilinear mixing model for nonlinear spectral unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 240-251, 2016.
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.
R. Heylen and Scheunders, P., Multi-dimensional pixel purity index for convex hull estimation and endmember extraction, IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 7, pp. 4059-4069, 2013.
J. Driesen and Scheunders, P., A Multicomponent Image Segmentation Framework, Lecture Notes in Computer Science, vol. 5259, pp. 589-600, 2008.
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.
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)
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.
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.
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.
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.

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