Publications

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Conference Paper
R. Heylen, Parente, M., and Scheunders, P., “Pixel purity vertex component analysis”, in IEEE IGARSS 2017, International Geoscience and Remote Sensing Symposium, Fort Worth, USA, July 23-28, 2017.
W. Fortes, Sijbers, J., and Batenburg, K. J., “Practical Error Bounds for Binary Tomography”, in 1st International Conference on Tomography of Materials and Structures, 2013, pp. 97-100.PDF icon Download paper (165.74 KB)
B. Auer, Könik, A., Fromme, T. J., Kalluri, K., De Beenhouwer, J., Zubal, G. I., Furenlid, L. R., and King, M. A., “Preliminary evaluation of surface mesh modeling of system geometry, anatomy phantom, and source activity for GATE simulations”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.
B. Auer, De Beenhouwer, J., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., “Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Manchester, UK, 2019.
B. Auer, De Beenhouwer, J., Fromme, T. J., Kalluri, K., Goding, J. C., Zubal, G. I., Furenlid, L. R., and King, M. A., “Preliminary investigation of design parameters of an innovative multi- pinhole system dedicated to brain SPECT imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., “A preliminary study of diffusion tensor imaging and tractography of the spinal cord in elderly”, in 21th Annual Symposium - Belgian Hospital Physicists Association, Ghent, Belgium, 2006, p. 61.
J. Sijbers, Scheunders, P., Van Dyck, D., and Raman, E., “Proceedings of the Royal Microscopical Society”, in Optimization of the SNR in NMR images using image sequences, London, UK, 1994, vol. 29, p. 232.
K. J. Batenburg, Palenstijn, W. J., and Sijbers, J., “Projection and backprojection in tomography: design choices and considerations”, in Workshop on Applications of Discrete Geometry and Mathematical Morphology, 2010, pp. 106-110.PDF icon Download paper (367.34 KB)
J. Sanctorum, Nguyen, V., Sijbers, J., Van Wassenbergh, S., and Dirckx, J. J. J., “Projection angle adapted distortion correction in high-speed image-intensifier based tomography”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (818.64 KB)
A. Dabravolski, De Beenhouwer, J., and Sijbers, J., “Projection-based polygon estimation in X-ray computed tomography”, in 6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS), 2016, pp. 41-50.PDF icon Download paper (615.72 KB)
H. Le, Bossuyt, C., Escoda, J., Costin, M., De Beenhouwer, J., and Sijbers, J., “Proximal Neural Networks based reconstruction for few-view CT applications”, in 14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium, 2025.PDF icon Download paper (4.27 MB)
E. Van de Casteele, Parizel, P. M., and Sijbers, J., “Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique”, in SPIE Medical Imaging, 2012, vol. 8313.PDF icon Download abstract (453.01 KB)
A. J. den Dekker, Sijbers, J., and Van Dyck, D., “Quantitative HREM: viewpoints on resolution, precision, and experimental design”, in Acta Cryst. A55 Supplement, Abstract M11.OE.OO5, IUCR Glasgow, Scotland, 1999.
L. - P. Lumbeeck, Paramonov, P., Sijbers, J., and De Beenhouwer, J., “The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape”, in IEEE ICIP, 2020, pp. 3040-3044.PDF icon Download paper (692.64 KB)
G. Van Gompel, Defrise, M., and Batenburg, K. J., “Reconstruction of a uniform star object from interior X-ray data”, in Nuclear Science Symposium Conference Record, NSS08, IEEE, Dresden, Germany, 2008, pp. 4115-4119.
E. Ribeiro Sabidussi, Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as Inverse Problem Solvers for MR Relaxometry”, in MIDL 2021 - Medical Imaging with Deep Learning, 2021.
J. Sijbers and Postnov, A., “Reduction of ring artifacts in high resolution micro-CT images”, in Advanced Concepts for Intelligent Vision Systems (ACIVS), Brussels, Belgium, 2004.
G. Van Eyndhoven, Batenburg, K. J., and Sijbers, J., “Region based 4D tomographic image reconstruction: application to cardiac X-ray CT”, in IEEE International Conference on Image Processing, 2015, pp. 113 - 117.PDF icon Download paper (708.79 KB)
A. - T. Nguyen, Renders, J., Sijbers, J., and De Beenhouwer, J., “Region-based motion-compensated iterative reconstruction technique for dynamic computed tomography”, in IEEE International Symposium on Biomedical Imaging (ISBI), Cartagena de Indias, Colombia, 2023.
V. Van Nieuwenhove, De Beenhouwer, J., Vlassenbroeck, J., Moesen, M., Brennan, M., and Sijbers, J., “Registration Based SIRT: A reconstruction algorithm for 4D CT”, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (2.36 MB)
J. Sijbers, Michiels, I., Van Audekerke, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Restoration of EEG signals distorted during simultaneous MR acquisitions”, in Proceedings of the International Society of Magnetic Resonance in Medicine, Denver CO, USA, 2000, p. 118.
J. Sijbers, Michiels, I., Verhoye, M., Van Audekerke, J., Van Der Linden, A., and Van Dyck, D., “Restoration of EEG signals distorted during simultaneous MR acquisitions”, in annual meeting: Magnetic Resonance Materials in Physics, Biology, and Medicine, Sevilla, Spain, 1999, p. 212.
P. Kempeneers, Sterckx, S., Debruyn, W., Park, Y., Ruddick, K., De Backer, S., and Scheunders, P., “Retrieval of oceanic constituents from ocean color using simulated annealing”, in IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, 25-29 July, 2005, vol. 8, pp. 5651-5654.
M. Nauwynck, Bazrafkan, S., Van Heteren, A., De Beenhouwer, J., and Sijbers, J., “Ring Artifact Reduction in Sinogram Space Using Deep Learning”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (2.49 MB)
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., “Ringing Artefact Removal From Sparse View Tomosynthesis using Deep Neural Networks”, in The 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 380-383.PDF icon Download paper (570.79 KB)

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