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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)
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.
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.
P. Scheunders, “Wavelet thresholding of multispectral images”, in Proc. ACIVS03, Andvanced Concepts for intelligent vision systems , Ghent, 2003, pp. 255-259.
P. Scheunders, “Multiscale fundamental forms: a multimodal image wavelet representation”, in Proc. ICIAP, International Conference on Image Analysis and Processing, Palermo, Italy, 2001, pp. 179-184.
P. Scheunders, De Clerck, N., and Wille, J., “Computerized image storage and analysis of contracting cardiac myocytes”, Journal of Computer Assisted Microscopy, vol. 6, pp. 77-83, 1994.
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., “Wavelet Denoising of multicomponent images using a noise-free image”, in ICIP’06, IEEE International Conference on Image Processing, Atlanta, Georgia, October 8-11, 2006, pp. 2619-2622.
P. Scheunders, De Backer, S., and Naud, A., “Non-linear mapping for feature extraction”, Lecture Notes in Computer Science, vol. 1451, pp. 823-830, 1998.
P. Scheunders and De Backer, S., “Wavelet-based enhancement of remote sensing and biomedical image series using an auxiliary image”, in SPIE Optics East, 23-26 October, Boston, Massachusetts USA, 2005, vol. 6001, pp. 41-52.
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, “Multiscale Edge Representation Applied to Image Fusion”, in Proc. Wavelet Applications in Signal and Image Processing VIII, 2000, pp. 894-901.
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 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., “Wavelet Denoising of multicomponent images using a Gaussian Scale Mixture model”, in ICPR’06, International Conference on Pattern Recognition, Hong Kong, august 20-24, 2006, vol. 3, pp. 754-757.

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