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Journal Article
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.
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)
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)
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., “Diffusion MRI fiber tractography of the brain”, NMR in Biomedicine, 2019.
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)
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.
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.
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.
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.
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)
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.
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.
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. 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)
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)
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.
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. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., “Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields”, Remote Sensing, vol. 11, 2019.PDF icon remotesensing-11-00624.pdf (1.5 MB)
D. Perrone, Jeurissen, B., Aelterman, J., Roine, T., Sijbers, J., Pizurica, A., Leemans, A., and Philips, W., “D-BRAIN: Anatomically Accurate Simulated Diffusion MRI Brain Data”, PlosOne, vol. 11, pp. 1-23, 2016.PDF icon Download paper (16.22 MB)
V. Van Nieuwenhove, De Beenhouwer, J., De Schryver, T., Van Hoorebeke, L., and Sijbers, J., “Data-Driven Affine Deformation Estimation and Correction in Cone Beam Computed Tomography”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1441-1451, 2017.
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P., and Gloaguen, R., “Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm”, Remote Sensing, vol. 12 (23), no. 4007, 2020.PDF icon remotesensing-12-04007-v2.pdf (21.88 MB)
A. J. den Dekker and Sijbers, J., “Data distributions in magnetic resonance images: a review”, Physica Medica, vol. 30, no. 7, pp. 725–741, 2014.PDF icon Download paper (410.33 KB)PDF icon Download paper (protected) (505.58 KB)
K. J. Batenburg, Sijbers, J., Poulsen, H. F., and Knudsen, E., “DART: A Robust Algorithm for Fast Reconstruction of 3D Grain Maps”, Journal of Applied Crystallography, vol. 43, pp. 1464-1473, 2010.PDF icon Download paper (824.99 KB)
K. J. Batenburg and Sijbers, J., “DART: A practical reconstruction algorithm for discrete tomography”, IEEE Transactions on Image Processing, vol. 20, pp. 2542-2553, 2011.PDF icon Download paper (2.12 MB)
K. Zarei Zefreh, Van Aarle, W., Batenburg, K. J., and Sijbers, J., “DART: a new approach for super-resolution reconstruction of license plates”, Journal of Electronic Imaging, vol. 22, no. 4, 2013.PDF icon Download paper (2.03 MB)

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