Publications

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E. Ribeiro Sabidussi, 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, in MIDL 2021 - Medical Imaging with Deep Learning, 2021.
E. Ribeiro Sabidussi, Klein, S., Jeurissen, B., and Poot, D. H. J., dtiRIM: A generalisable deep learning method for diffusion tensor imaging, Neuroimage, vol. 269, 2023.PDF icon Download paper (5.11 MB)
C. C. Sabino, Andrade, L. S., Tsang, I. R., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., Motion Compensation Techniques in Permutation-Based Video Encryption, in Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics, Washington, DC, USA, 2013, pp. 1578–1581.
C. A. Sage, Van Hecke, W., Peeters, R. R., Sijbers, J., Robberecht, W., Parizel, P. M., Marchal, G., Leemans, A., and Sunaert, S., Quantitative diffusion tensor imaging in amyotrophic lateral sclerosis: revisited., Human brain mapping, vol. 30, no. 11, pp. 3657-75, 2009.
K. Rafiezadeh Sahi, Rasti, B., Ghamisi, P., Scheunders, P., and Gloaguen, R., When is the right time to apply denoising?, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
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)
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)
K. Rafiezadeh Sahi, Ghamisi, P., Jackisch, R., Rasti, B., Scheunders, P., and Gloaguen, R., A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 15, pp. 284-296, 2022.PDF icon mdc_jstars-final_version.pdf (6.53 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., Hyperspectral clustering using atrous spatial-spectral convolutional network, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
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.
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography, Measurement Science and Technology, vol. 32, no. 035404, pp. 1-11, 2021.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., Dark field sensitivity in single mask edge illumination lung imaging, in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 2021, pp. 775-778.
J. Sanctorum, De Beenhouwer, J., and Sijbers, J., X-ray phase contrast simulation for grating-based interferometry using GATE, Optics Express, vol. 28, no. 22, pp. 33390-33412, 2020.PDF icon Download paper (2.5 MB)
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)
J. Sanctorum, Six, N., Sijbers, J., and De Beenhouwer, J., Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, San Diego, USA, 2022, p. 1224218.PDF icon Download paper (303.24 KB)
J. Sanctorum, Janssens, E., den Dekker, A. J., Senck, S., Heinzl, C., De Beenhouwer, J., and Sijbers, J., A workflow to reconstruct grating-based X-ray phase contrast CT images: application to CFRP samples, 4th Conference on X-ray and Neutron Phase Imaging with Gratings. Zürich, Switzerland, pp. 139-140, 2017.PDF icon Download poster (1008.67 KB)PDF icon Download abstract (294.87 KB)
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique, Physics in Medicine and Biology, vol. 66, no. 16, 2021.PDF icon Download paper (4.28 MB)
J. Sanctorum, De Beenhouwer, J., and Sijbers, J., X-ray Phase-contrast Simulations of Fibrous Phantoms using GATE, in 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Sydney, Australia, 2018.PDF icon Download poster (884.48 KB)
J. Sanctorum, Nguyen, V., Sijbers, J., Van Wassenbergh, S., and Dirckx, J. J. J., Projection angle adapted distortion correction in high-speed image-intensifier based tomography, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (818.64 KB)
J. Sanctorum, De Beenhouwer, J., Weissenböck, J., Heinzl, C., Kastner, J., and Sijbers, J., Simulated grating-based x-ray phase contrast images of CFRP-like objects, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019, pp. 1-8.PDF icon Download paper (706.73 KB)
S. Scataglini, Danckaers, F., Huysmans, T., Sijbers, J., and Andreoni, G., Design smart clothing using digital human models, in DHM and Posturography, Academic Press, 2019, pp. 683-698.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., Sijbers, J., and Andreoni, G., Using 3D Statistical Shape Models for Designing Smart Clothing, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 18–27.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., and Sijbers, J., Moving Statistical Body Shape Models Using Blender, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 28–38.
P. Scheunders and Sijbers, J., Multiscale watershed segmentation of multivalued images, in Proc. ICPR02, International Conference on Pattern Recognition, Quebec, Canada, 2002, vol. 3, pp. 855-858.

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