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E. Van de Casteele, Bugani, S., Camaiti, M., Morselli, L., and Janssens, K., “X-ray microtomography as a non-destructive tool for stone characterization in a conservation study”, in 4th ICNDT Hellenic Society, 2007.
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “Modelling of Beam hardening in micro CT”, in IEEE International Symposium on Biomedical Imaging, Washington DC, USA, 2003, pp. 57-58.PDF icon Download full paper (163.52 KB)
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “A bimodal energy model for correcting beam hardening artefacts in X-ray tomography”, in IEEE 29th Annual Northeast Bioengineering Conference2003 IEEE 29th Annual Proceedings of Bioengineering Conference, Newark, NJ, USA, 2003, pp. 57 - 58.
E. Van de Casteele, Bugani, S., Van Der Linden, A., and Janssens, K., “X-ray microtomography as an imaging tool in cultural heritage”, 9th International Conference on NDT of Art. 2008.
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “A model-based correction method for beam hardening artefacts in X-ray microtomography”, Journal of X-ray science and technology, vol. 12, pp. 53-57, 2004.PDF icon Download full paper (632.04 KB)
T. Van De Looverbosch, Jiaqi, H., Tempelaere, A., Kelchtermans, K., Verboven, P., Tuytelaars, T., Sijbers, J., and Nicolai, B., “Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images”, Computers and Electronics in Agriculture, vol. 197, no. 106962, pp. 1-14, 2022.
T. Van De Looverbosch, De Beuckeleer, S., De Smet, F., Sijbers, J., and De Vos, W., “Proximity Adjusted Centroid Mapping for Accurate Detection of Nuclei in Dense 3D Cell Systems”, Computers in Biology and Medicine, vol. 185, p. 109561, 2025.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., “Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning”, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., “Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning”, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 2021.
G. Van de Wouwer, Livens, S., Scheunders, P., and Van Dyck, D., “Color texture classification by wavelet energy-correlation signatures”, in Proc. ICIAP Intern. Conf. On Computer Analysis and Image Processing , Florence, Italy, 17-19 september, 1997, pp. 327-334.
G. Van de Wouwer, Scheunders, P., Livens, S., and Van Dyck, D., “Wavelet correlation signatures for color texture characterization”, pattern Recognition, vol. 32, pp. 443-451, 1999.
G. Van de Wouwer, Scheunders, P., Van Dyck, D., Bodt, D. M., Wuyts, F. L., and Van de Heyning, P. H., “Wavelet-FILVQ classifier for speech analysis”, in Proc. ICPR'96 Internat. Conference on Pattern Recognition , D, pp. 214-218, Vienna, august 25-30, 1996, pp. 214-218.
G. Van de Wouwer, Scheunders, P., and Van Dyck, D., “Rotation-Invariant Texture Characterization using Isotropic Wavelet Frames”, in Proc. ICPR98, International Conference on Pattern Recognition , Brisbane, Australia, 17-20 august, 1998, pp. 814-816.
G. Van de Wouwer and Scheunders, P., “Wavelet-based texture classification”, Recent Research in the Development of Pattern Recognition, vol. 1, pp. 77-87, 2000.
G. Van de Wouwer, Vautrot, P., Scheunders, P., Livens, S., Van Dyck, D., and Bonnet, N., “Rotation-invariant texture segmentation using continuous wavelets”, in Proc. 2-nd IEEE Symposium on applications of time-frequency and time-scale methods , Coventry, UK, 27-29/9, 1997.
G. Van de Wouwer, Scheunders, P., and Van Dyck, D., “Statistical texture characterization from discrete wavelet representations”, IEEE Transactions on Image Processing, vol. 8, pp. 592-598, 1999.
G. Van de Wouwer, Weyn, B., Scheunders, P., Jacob, W., Van Marck, E., and Van Dyck, D., “Automated chromatin-texture based diagnosis of carcinoma nuclei”, Journal of Microscopy, vol. 197, pp. 25-35, 2000.
G. Van de Wouwer, Scheunders, P., Van Dyck, D., Wuyts, F. L., and Van de Heyning, P. H., “Voice recognition from spectrograms: a wavelet based approach”, Fractals, vol. 5, pp. 165-172, 1997.
G. Van de Wouwer, Scheunders, P., Van Dyck, D., Wuyts, F. L., and Van de Heyning, P. H., “Voice classification by wavelet transforms and fuzzy interpreted LVQ networks”, in Proceedings International Symposium on Soft Computing and Intelligent Industrial Automation, Reading, UK, March 26-28, 1996, pp. 171-177.
W. Van den Broek, Rosenauer, A., Sijbers, J., Van Dyck, D., and Van Aert, S., “A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM Ultramicroscopy”, Ultramicroscopy, vol. 141, pp. 22–31, 2014.
W. Van den Broek, Verbeeck, J., Schryvers, D., De Backer, S., and Scheunders, P., “Tomographic Spectroscopic Imaging; an experimental proof of concept”, Ultramicroscopy, vol. 109, pp. 296-303, 2009.
W. Van den Broek, Verbeeck, J., De Backer, S., Scheunders, P., and Schryvers, D., “Acquisition of the EELS data cube by tomographic reconstruction”, Ultramicroscopy, vol. 106, pp. 269-276, 2006.
S. Van der Jeught, “Optical techniques for real-time morphology measurement of the tympanic membrane”, 2015.
S. Van der Jeught, Sijbers, J., and Dirckx, J. J. J., “Fast Fourier-based phase unwrapping on the graphics processing unit in real-time imaging applications”, Journal of Imaging, vol. 1, pp. 31-44, 2015.PDF icon Download paper (1.35 MB)
A. Van Der Linden, Van de Casteele, E., Thomas, M. S., Vos, A., Janssen, E., and Janssens, K., “Analysis of micro computed tomography images; a look inside historic enamelled metal objects”, Applied Physics A, vol. 98, no. 2, pp. 385 - 392, 2010.

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