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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, 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)
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, “Bayesian techniques for multi/hyperspectral image processing”, in 4th IEEE Conference on Industrial Electronics and Applications, Xi’an, China, May 25-27, 2009, pp. 1-10.
P. Scheunders, “Comparison of clustering algorithms applied to colour image quantization”, Pattern Recognition Letters, vol. 18, pp. 1379-1384, 1997.
P. Scheunders and De Backer, S., “High-dimensional clustering using frequency sensitive competitive learning”, Pattern Recognition, vol. 32, pp. 193-202, 1999.
P. Scheunders, “Local mapping for multispectral image visualisation”, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
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 Sijbers, J., “Multiscale watershed segmentation of multivalued images”, in Proc. ICPR02, International Conference on Pattern Recognition, Quebec, Canada, 2002, vol. 3, pp. 855-858.
P. Scheunders and De Backer, S., “Joint quantization and error-diffusion of color images using competitive learning”, in Proc. IEEE Conference on Image Processing , Santa Barbara, 26-29 october, 1997, pp. 811-814.
P. Scheunders, “Joint quantization and error-diffusion of color images using competitive learning”, Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, pp. 137-140, 1998.
P. Scheunders, Tuia, D., and Moser, G., “Contributions of Machine Learning to Remote Sensing Data Analysis”, in Comprehensive Remote Sensing, vol. 2, 2018, pp. 199-243.
P. Scheunders and Sijbers, J., “Multiscale anisotropic filtering of color images”, in Proceedings of the IEEE International Conference on Image Processing, Thessaloniki, Greece, 2001, vol. 3, pp. 170-173.

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