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Conference Paper
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., A comparison of diffusion tensor analysis methods for detecting age-related changes of the normal appearing spinal cord, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 293-294.
M. Van Dael, Verboven, P., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., Comparison of methods for online inspection of apple internal quality, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (815.39 KB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
S. Hassanzadeh, Karami, A., Heylen, R., and Scheunders, P., Compression Of Hyperspectral Images Using Block Coordinate Descent Search And Compressed Sensing, in 8th workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, Los Angeles, USA, 2016.
N. Francken, Sanctorum, J., Renders, J., Paramonov, P., Sijbers, J., and De Beenhouwer, J., A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations, in 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023.PDF icon Download paper (4.14 MB)
G. Van Gompel, Defrise, M., and Van Dyck, D., Consistent Extrapolation of Truncated 2D CT Projections, in Micro tomography 3D, Gasthuisberg, Leuven, Belgium, 2006.
J. Sijbers, Raman, E., Van Audekerke, J., Malfliet, W., Van Der Linden, A., Verhoye, M., and Cloeck, C., The construction of a gradient set, in 4th Meeting of the FGWO/FRSM Contact Group Biomedical MR, Louvain-la-Neuve, Belgium, 1993, p. 5.
W. Van Hecke, Leemans, A., De Backer, S., Parizel, P. M., and Sijbers, J., On the construction of a ground truth methodology to evaluate VBM analysis results of diffusion tensor images, in European Society for Magnetic Resonance in Medicine and Biology, Valencia, Spain, 2008.
W. Van Hecke, D'Agostino, E., Leemans, A., Parizel, P. M., Maes, F., and Sijbers, J., On the construction of a healthy brain inter-subject diffusion tensor image and tractography atlas, in 32nd Congress of the Europea Society of NeuroRadiolog, 2007, p. 146.
J. Sijbers and den Dekker, A. J., Construction of a likelihood ratio test for magnitude fMRI data, in 19th Annual Symposium of the Belgian Hospital Physicists Association, 2004.
J. Cant, Behiels, G., and Sijbers, J., Continuous Digital Laminography, in 6th Conference on Industrial Computed Tomography, Wels, Austria, 2016.PDF icon Download paper (363.74 KB)
W. D'haes, Van Dyck, D., and Rodet, X., Control Parameter Estimation for a Physical Model of a Trumpet Using Pattern Recognition, in IEEE Workshop on Model Based Processing and Coding of Audio (MPCA), Leuven, Belgium, 2002.
L. F. Alves Pereira, Dabravolski, A., Tsang, I. R., Cavalcanti, G. D. C., and Sijbers, J., Conveyor belt X-ray CT using Domain Constrained Discrete Tomography, in Sibgrapi conference on Graphics, Patterns and Images, 2014, pp. 290 - 297.PDF icon Download paper (3.45 MB)
J. Sijbers, Van Camp, N., Leemans, A., den Dekker, A. J., Verhoye, M., and Van Der Linden, A., Coregistration of Micro-MRI, microCT and microPET, in Workshop on non Invasive 3D Microscopy, University of Antwerp, Belgium, 2004, p. 16.
F. Danckaers, Huysmans, T., Lacko, D., Ledda, A., Verwulgen, S., Van Dongen, S., and Sijbers, J., Correspondence Preserving Elastic Surface Registration with Shape Model Prior, in International Conference of Pattern Recognition, 2014, vol. 22, pp. 2143-2148.PDF icon paper (550.57 KB)
Z. Bnoulkacem, Vlaminck, M., Morocho, G. Raimundo L., Zivariadab, H., Zahiri, Z., Koirala, B., Platisa, L., Luong, H., Scheunders, P., Mangialetto, F., and Bufi, I., Corrosion detection using hyperspectral VNIR and SWIR imaging for drone-based inspection of electrical pylons, in EUROCORR 2023, European Corrosion Congress, Proceedings, 2023, p. 2.
S. Livens, Anthonis, A., Mahy, M., and Scheunders, P., Cross-media tonal mapping model obtained from psychometric experiments, in Proc. SPIE 5008: Color Imaging, Device- Independent Color, Color Hardcopy, and Graphic Arts VII , Santa Clara, CA, 2003, pp. 14-23.
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.
K. J. Batenburg and Sijbers, J., DART: a fast heuristic algebraic reconstruction algorithm for discrete tomography, in Proceedings of the IEEE International Conference on Image Processing (ICIP), San Antonio, Texas, USA, 2007.PDF icon Download paper (415.32 KB)
R. Pinho, Tournoy, K. G., Gosselin, R., and Sijbers, J., A Decision Support System for the Treatment of Tracheal Stenosis, in Proc. of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM), Istanbul, 2010, pp. 72-76.
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., Deep Blind Unmixing using Minimum Simplex Convolutional Network, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 28-31.PDF icon misicnet_igarss2022.pdf (1.29 MB)
L. F. Alves Pereira, Van Nieuwenhove, V., De Beenhouwer, J., and Sijbers, J., A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
J. Van Houtte, Bazrafkan, S., Vandenberghe, F., Zheng, G., and Sijbers, J., A Deep Learning Approach to Horse Bone Segmentation from Digitally Reconstructed Radiographs, in International Conference on Image Processing Theory, Tools, and Applications, 2019.
A. Presenti, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
L. F. Alves Pereira, De Beenhouwer, J., and Sijbers, J., The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis, in 31st European Signal Processing Conference, EUSIPCO, 2023.