Jan Sijbers

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Conference Paper
F. Danckaers, Van Houtte, J., Booth, B. G., Verstreken, F., and Sijbers, J., Statistical shape and pose model of the forearm for custom splint design, in IEEE International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1669-1672.PDF icon Download paper (1.54 MB)
Conference Abstract
C. Smekens, Beirinckx, Q., Vanhevel, F., Van Dyck, P., den Dekker, A. J., Sijbers, J., Janssens, T., and Jeurissen, B., Super-resolution T2* mapping of the knee using UTE Spiral VIBE MRI, Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), 29th Annual Meeting, An Online Experience. p. 3920, 2021.
Conference Paper
D. Frenkel, De Beenhouwer, J., and Sijbers, J., Tabu-DART: an dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
Journal Article
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., To Recurse or not to Recurse A Low Dose CT Study, Progress in Artificial Intelligence, vol. 10, pp. 65–81, 2021.
Conference Paper
V. Nguyen, De Beenhouwer, J., Bazrafkan, S., Hoang, A. - T., Van Wassenbergh, S., and Sijbers, J., BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 518-521.PDF icon Download paper (2.16 MB)
M. Ljubenović, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., CNN-based Deblurring of Terahertz Images, in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2020, vol. 4, pp. 323-330.PDF icon Download paper (16.31 MB)
T. Peeters, Vleugels, J., Verwulgen, S., Danckaers, F., Huysmans, T., Sijbers, J., and De Bruyne, G., A Comparative Study Between Three Measurement Methods to Predict 3D Body Dimensions Using Shape Modelling, in Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping, Cham, 2020, vol. 975, pp. 464–470.
Conference Paper
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.

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