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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)
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 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, 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 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.
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., “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 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.
P. Scheunders, “Comparison of clustering algorithms applied to colour image quantization”, Pattern Recognition Letters, vol. 18, pp. 1379-1384, 1997.
P. Scheunders, “A genetic approach towards optimal color image quantization”, in Proc. ICIP'96, IEEE Internat. Conference on Image Processing , III, Lausanne, september 16-19, 1996, pp. 1031-1034.
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, “Local mapping for multispectral image visualisation”, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
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, “A wavelet representation of multispectral images; in: Frontiers of Remote Sensing Information Processing”, C. H. Chen, Ed. World Scientific, 2003, pp. 197-224.
P. Scheunders, “Genetic optimal quantization of gray-level and color images”, in Proceedings ACCV'95, Second Asian Conference on Computer Vision, Singapore, 5-8 december, 1995, pp. 94-98.
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, “Wavelet representations of multivalued images”, in Wavelet Applications in Industrial Processing, part of the International Symposium on Photonics Technologies for Robotics, Automation, and Manufacturing , 27-31 October 2003, Providence, RI USA, 2003, pp. 203-215.

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