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Journal Article
J. Van Houtte, Audenaert, E., Zheng, G., and Sijbers, J., “Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images”, International Journal of Computer Assisted Radiology and Surgery, vol. 309, pp. 1333–1342, 2022.PDF icon Download paper (3.41 MB)
V. Varkarakis, Bazrafkan, S., and Corcoran, P., “Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets”, Science Direct Elsevier Neural Networks, vol. 121, pp. 101-121, 2020.
M. Yosifov, Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations”, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.PDF icon Download paper (2.37 MB)
J. Veraart, Novikov, D. S., Daan, C., Ades-Aron, B., Sijbers, J., and Fieremans, E., “Denoising of diffusion MRI using random matrix theory”, NeuroImage, vol. 142, pp. 384-396, 2016.PDF icon Download paper (4.53 MB)
S. De Backer, Pizurica, A., Huysmans, B., Philips, W., and Scheunders, P., “Denoising of Multicomponent Images Using Wavelet Least-Squares Estimators”, Image and Vision Computing, vol. 26, pp. 1038-1051, 2008.
J. Gonnissen, De Backer, A., den Dekker, A. J., Sijbers, J., and Van Aert, S., “Detecting and locating light atoms from high-resolution STEM images: the quest for a single optimal design Ultramicroscopy”, Ultramicroscopy, vol. 170, pp. 128-138, 2016.
D. Burazerovic, Geens, B., Heylen, R., Sterckx, S., and Scheunders, P., “Detecting the adjacency effect in hyperspectral imagery with spectral unmixing techniques”, IEEE JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 3, pp. 1070-1078, 2013.
H. Struyfs, Van Hecke, W., Veraart, J., Sijbers, J., Slaets, S., De Belder, M., Wuyts, L., Peters, B., Sleegers, K., Robberecht, C., Van Broeckhoven, C., De Belder, F., Parizel, P. M., and Engelborghs, S., “Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?”, Journal of Alzheimer’s Disease, vol. 48, pp. 937-948, 2015.PDF icon Download paper (374.95 KB)
J. Praet, Manyakov, N., Muchene, L., Mai, Z., Terzopoulos, V., De Backer, S., Torremans, A., Guns, P. - J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D., Schmidt, M., Van Der Linden, A., and Verhoye, M., “Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology.”, Alzheimer's Research & Therapy , vol. 10, no. 1, pp. 1-16, 2018.
S. Van Cauter, Veraart, J., Sijbers, J., Peeters, R. R., Himmelreich, U., Gool, V. S., Van Calenbergh, F., De Vleeschouwer, S., Van Hecke, W., and Sunaert, S., “Diffusion kurtosis imaging in the grading of gliomas”, Radiology, vol. 2, pp. 492-501, 2012.
C. Guglielmetti, Veraart, J., Roelant, E., Mai, Z., Daans, J., Van Audekerke, J., Naeyaert, M., Vanhoutte, G., Delgado Y Palacios, R., Praet, J., Fieremans, E., Ponsaerts, P., Sijbers, J., Van Der Linden, A., and Verhoye, M., “Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination”, NeuroImage, vol. 125, pp. 363–377, 2016.
G. Vanhoutte, Pereson, S., Delgado Y Palacios, R., Guns, P. - J., Asselbergh, B., Veraart, J., Sijbers, J., Verhoye, M., Van Broeckhoven, C., and Van Der Linden, A., “Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer's disease”, Magnetic Resonance in Medicine, vol. 69, no. 4, pp. 1115–1121, 2013.
Q. Collier, Veraart, J., Jeurissen, B., Vanhevel, F., Pullens, P., Parizel, P. M., den Dekker, A. J., and Sijbers, J., “Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach”, Magnetic Resonance in Medicine, vol. 80, no. 2, pp. 802-813, 2018.PDF icon Download paper (1.93 MB)
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., “Diffusion MRI fiber tractography of the brain”, NMR in Biomedicine, 2019.
Z. Mai, Verhoye, M., Van Der Linden, A., and Sijbers, J., “Diffusion tensor image up-sampling: a registration-based approach”, Magnetic resonance Imaging, vol. 28, pp. 1497-1506, 2010.PDF icon Download paper (814.96 KB)
W. Van Hecke, Nagels, G., Emonds, G., Leemans, A., Sijbers, J., van Goethem, J., and Parizel, P. M., “A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions.”, Journal of magnetic resonance imaging : JMRI, vol. 30, no. 1, pp. 25-34, 2009.PDF icon Download paper (902.67 KB)
N. Van Camp, Blockx, I., Verhoye, M., Casteels, C., Coun, F., Leemans, A., Sijbers, J., Baekelandt, V., Van Laere, K., and Van Der Linden, A., “Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract.”, NMR in biomedicine, vol. 22, no. 7, pp. 697-706, 2009.
P. Van Dyck, Froeling, M., Heusdens, C. H. W., Sijbers, J., Ribbens, A., and Billiet, T., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study”, Journal of Orthopaedic Research , vol. 39, pp. 1318–1330, 2021.
P. Van Dyck, Billiet, T., Desbuquoit, D., Verdonk, P., Heusdens, C. H., Roelant, E., Sijbers, J., and Froeling, M., “Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study”, European Radiology, vol. 34, pp. 6673–6684, 2020.
P. Van Dyck, Froeling, M., De Smet, E., Pullens, P., Torfs, M., Verdonck, P., Sijbers, J., Parizel, P. M., and Jeurissen, B., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft”, Journal of Magnetic Resonance Imaging, vol. 46, no. 5, pp. 1423–1432, 2017.
J. Christopher, Lumbeeck, L. - P., Paramonov, P., De Beenhouwer, J., and Sijbers, J., “Discrete Terahertz tomography: a simulation study”, e-Journal of Nondestructive Testing, vol. 27, no. 3, 2022.PDF icon Download paper (345.5 KB)
E. Van de Casteele, Perilli, E., Van Aarle, W., Reynolds, K., and Sijbers, J., “Discrete tomography in an in vivo small animal bone study”, Journal of Bone and Mineral Metabolism, vol. 36, no. 1, pp. 40–53, 2018.
H. Segers, Palenstijn, W. J., Batenburg, K. J., and Sijbers, J., “Discrete Tomography in MRI: a Simulation Study”, Fundamenta Informaticae, vol. 125, no. 3-4, pp. 223-237, 2013.
A. Smolders, Martino, D. F., Staeren, N., Scheunders, P., Sijbers, J., Goebel, R., and Formisano, E., “Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis”, Magnetic Resonance Imaging, vol. 25, pp. 860-868, 2007.PDF icon Download paper (658.36 KB)
R. Heylen and Scheunders, P., “A distance geometric framework for non-linear hyperspectral unmixing”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, pp. 1879-1888, 2014.

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