Publications

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Conference Paper
Z. Mai, Verhoye, M., Van Der Linden, A., and Sijbers, J., “Diffusion Tensor Images Upsampling: a Registration-based Approach”, in 13th International Machine Vision and Image Processing Conference, Dublin, Ireland, 2009, vol. 13, pp. 36-40.PDF icon Download paper (808.21 KB)
Z. Mai, Verhoye, M., and Sijbers, J., “Diffusion Tensor Images Edge-Directed Interpolation”, in International Symposium on Biomedical Imaging 2010, 2010, pp. 732-735.
W. Van Hecke, Leemans, A., De Brabander, N., Laridon, A., Claeys, K., Ceulemans, B., Van Goethem, J., Parizel, P. M., and Sijbers, J., “Diffusion Tensor Fiber Tracking Reveals Probst Bundles in Patients with Agenesis of the Corpus Callosum”, in 32nd Congress of the Europea Society of NeuroRadiolog, 2007, p. 135.
W. Van Hecke, Leemans, A., De Brabander, N., Laridon, A., Ceulemans, B., Sijbers, J., and Parizel, P. M., “Diffusion tensor fiber tracking in patients with agenesis of the corpus callosum”, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 34-35.
A. J. den Dekker and Sijbers, J., “Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test”, in Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, 2004, pp. 233-236.
S. Delputte, Leemans, A., Fieremans, E., De Deene, Y., D'Asseler, Y., Lemahieu, I., Achten, E., Sijbers, J., and Van de Walle, R., “Density Regularized Fiber Tractography of the Brain White Matter using Diffusion Tensor MRI”, in 13th Scientific Meeting - International Society for Magnetic Resonance in Medicine, Miami, USA, 2005, p. 1309.
J. Rajan, Jeurissen, B., Sijbers, J., and Kannan, K., “Denoising Magnetic Resonance Images using Fourth Order Complex Diffusion”, in 13th International Machine Vision and Image Processing Conference, Dublin, Ireland, 2009, pp. 123-127.
J. Renders, Shafieizargar, B., Verhoye, M., De Beenhouwer, J., den Dekker, A. J., and Sijbers, J., “DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data”, in IEEE International Symposium on Biomedical Imaging, 2023, pp. 1-4.
M. Yosifov, Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations”, in e-Journal of Nondestructive Testing, 2023, vol. 28, no. 3.PDF icon Download paper (2.37 MB)
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.
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.
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.
C. Bossuyt, den Dekker, A. J., Iuso, D., Le Hoang, T., Escoda, J., Costin, M., Sijbers, J., and De Beenhouwer, J., “Deep image prior for sparse-view reconstruction in static, rectangular multi-source x-ray CT systems for cargo scanning”, in SPIE Developments in X-Ray Tomography XV, 2024, vol. 13152.
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.
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.
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)
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.
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)
N. Francken, Sanctorum, J., Huyge, B., Sijbers, J., and De Beenhouwer, J., “Correcting for focal spot drift in edge illumination X-ray phase contrast imaging”, in 14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium, 2025.
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.
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. 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)
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.
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.
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.

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