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Conference Paper
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.
P. Scheunders, “Denoising of multispectral images using wavelet thresholding”, in Proc. SPIE conference on Image and Signal Processing for Remote Sensing IX, part of the International Symposium on Remote Sensing, Barcelona, Spain, 2003, pp. 28-35.
A. Karami, Heylen, R., and Scheunders, P., “Denoising Of Hyperspectral Images Using Shearlet Transform And Fully Constrained Least Squares Unmixing”, in 8th workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, Los Angeles, USA, 2016.
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.
H. Q. Nguyen, Nguyen, B. T., Dong, T. Q., Ngo, D. T., and Nguyen, A. - T., “Deep Q-Learning with Multiband Sensing for Dynamic Spectrum Access”, in IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Seoul, Korea, 2018.
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.
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)
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.
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.
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.PDF icon exhibit_17_corrosion_detection_using_hyperspectral_vnir_and_swir_imaging.pdf (138.17 KB)
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)
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)
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.
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.

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