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P. Scheunders, “An orthogonal wavelet representation of multivalued images”, in Proc. ACIVS02, Andvanced Concepts for intelligent vision systems, Ghent, 2002.
P. Scheunders and De Backer, S., “High-dimensional clustering using frequency sensitive competitive learning”, Pattern Recognition, vol. 32, pp. 193-202, 1999.
P. Scheunders, Duijster, A., and Zhang, Y., “Wavelet-based Multi/Hyperspectral Image Restoration and Fusion”, in Signal and Image Processing for Remote Sensing, C. H. Chen, Ed. Taylor and Francis, 2012, pp. 505-523.
P. Scheunders and Driesen, J., “Least squares interband denoising of color and multispectral images”, in Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore, 2004, pp. 985-988.
P. Scheunders, “Local mapping for multispectral image visualisation”, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
P. Scheunders, “Multiscale Edge Representation Applied to Image Fusion”, in Proc. Wavelet Applications in Signal and Image Processing VIII, 2000, pp. 894-901.
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.
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, 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, “Advances in Monte Carlo simulations for the design of X-ray phase contrast imaging systems”, 2026.PDF icon Downloald thesis (17.67 MB)
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, 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, 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, Sijbers, J., and De Beenhouwer, J., “Multi-contrast benchmarking of edge illumination Monte Carlo simulations using virtual gratings”, Journal of Applied Physics, vol. 137, no. 10, p. 104904, 2025.
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)
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.

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