Publications

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Conference Paper
W. Van Aarle, Batenburg, K. J., and Sijbers, J., “Threshold Selection for Segmentation of Dense Objects in Tomograms”, in International Symposium on Visual Computing, Berlin Heidelberg, 2008, vol. 5358, pp. 700-709.
J. Cant, Palenstijn, W. J., Behiels, G., and Sijbers, J., “Tomographic image reconstruction from continuous projections”, in The third international conference on image formation in X-ray computed tomography, Salt Lake City, USA, 2014, pp. 295-298.PDF icon Download paper (2.38 MB)
B. Fröhler, Melo, Lda Cunha, Weissenböck, J., Kastner, J., Möller, T., Hege, H. - C., Gröller, E., Sanctorum, J., De Beenhouwer, J., Sijbers, J., and Heinzl, C., “Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.07 MB)
W. Pintjens, Sijbers, J., Verhoye, M., Van Audekerke, J., and Van Der Linden, A., “A total correction scheme for EPI distortions at high field”, in 22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 328-329.
Z. Liang, Van Heteren, A., Sijbers, J., and De Beenhouwer, J., “Toward denoising of 3D CT scans with few data”, in e-Journal of Nondestructive Testing, 2023, vol. 28, no. 3.PDF icon Download paper (5.93 MB)
D. Burazerovic, Heylen, R., and Scheunders, P., “Towards streaming hyperspectral endmember extraction”, in IEEE IGARSS2011, IEEE International Geoscience and Remote Sensing Symposium , Vancouver, July 25-29, 2011.
K. J. Batenburg and Sijbers, J., “Trabecular bone reconstruction from micro-CT data using discrete tomography”, in Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium), Antwerp, Belgium, 2006, pp. 65-69.
R. Pinho, Huysmans, T., Vos, W., and Sijbers, J., “Tracheal Stent Prediction Using Statistical Deformable Models of Tubular Shapes”, in Proceedings of SPIE Medical Imaging, San Diego, CA, USA, 2008.PDF icon Full text (773.58 KB)
R. Pinho, Huysmans, T., Vos, W., and Sijbers, J., “Tracheal Stent Prediction Using Statistical Deformable Models of Healthy Tracheas”, in Liege Image Days 2008: Medical Imaging, 2008.PDF icon Full text (34.19 KB)
T. Nath, Liu, G., Weyn, B., Hassan, B., De Backer, S., and Scheunders, P., “Tracking for Quantifying Social Network of Drosophila Melanogaster”, in 15th Computer Analysis of Images and Patterns (CAIP), 2013, vol. 8048, pp. 539–545.
A. Leemans, De Backer, S., Sijbers, J., Vandervliet, E., and Parizel, P. M., “TRACT: Tissue Relative Anisotropy based Curvature Thresholding for deterministic MR diffusion tensor tractography”, in 22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology, Basle, Switzerland, 2005, p. 289.
T. Roine, Kaartinen, J., and Lamberg, P., “Training Simulator for Flotation Process Operators”, in 18th IFAC World Congress, 2011.
W. Liao, Huang, F., v. Coillie, F., Thoonen, G., Pizurica, A., Scheunders, P., and Philips, W., “Two-stage fusion of thermal hyperspectral and visible RGB image by PCA and guided filter”, in IEEE Whispers 2015, Workshop on Hyperspectral Image and Signal Processing, June 2-5, Tokyo, 2015.
H. N. B. Pinheiro, Tsang, I. R., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., “Type-2 fuzzy GMMs for robust text-independent speaker verification in noisy environments”, in International Conference of Pattern Recognition, 2014.
E. Bettens, den Dekker, A. J., Sijbers, J., and Van Dyck, D., “Ultimate resolution in the framework of parameter estimation”, in IASTED International Conference - Signal and Image Processing (SIP'98), Las Vegas, Nevada, USA, 1998, pp. 229-233.PDF icon Download paper (113.28 KB)
J. Sijbers, den Dekker, A. J., Scheunders, P., Raman, E., and Van Dyck, D., “Unbiased signal estimation in magnitude MR images”, in Proceedings of the European Society for Magnetic Resonance in Medicine and Biology, Brussels, Belgium, 1997, vol. 2, p. 174.
D. Burazerovic, Geens, B., Heylen, R., Sterckx, S., and Scheunders, P., “Unmixing for detection and quantification of adjacency effects”, in IEEE IGARSS2012, International Geoscience and Remote Sensing Symposium, Munich, July 22-27, 2012, pp. 3090-3093.
B. Koirala, Rasti, B., Bnoulkacem, Z., and Scheunders, P., “Unmixing Intimate Mixtures Using Bézier Surfaces”, in 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2023, pp. 1-5.PDF icon bezier.pdf (605.24 KB)
P. Kempeneers, De Backer, S., Delalieux, S., Sterckx, S., Debruyn, W., Coppin, P., and Scheunders, P., “Upscaling of spectroradiometer data for stress detection in orchards with remote sensing”, in SPIE Remote Sensing, Gran Canaria, 13-16 september, Maspalomas, Spain, 2004, vol. 127, pp. 37-45.
J. Sijbers, Scheunders, P., Van Dyck, D., and Raman, E., “The use of two NMR realizations for determining and improving of the image SNR”, in Proceedings of the Joint Meeting of the Belgian and Dutch Societies for Electron Microscopy, Arnhem, Papendal, The Netherlands, 1994, p. 65.
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.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., “Using diffusion tensor imaging (DTI) to assess the neuronal plasticity in the brain of a songbird”, in 4th Annual Symposium – Young Belgian Magnetic Resonance Scientists, Brussels, Belgium, 2005.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., “Using diffusion tensor imaging (DTI) to assess the neuronal plasticity and neuroconnectivity in the brain of a songbird”, in Molecular & Cellular Basis of Neuroconnectivity, Leuven, Belgium, 2006.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., “Using diffusion tensor imaging (DTI) to assess the neuronal plasticity in the brain of a songbird”, in XXeme Congres du Groupement d'Etudes de Resonance Magnetique, Blankenberge, Belgium, 2006.
C. C. Hung, Coleman, T., and Scheunders, P., “Using genetic differential competitive learning for unsupervised training in multispectral image classification systems”, in Proceedings IEEE International Conference on Systems, Man, and Cybernetics , San Diego, California, October 11-14, 1998, pp. 4482-4485.

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