Publications

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In Press
B. G. Booth, Keijsers, N. L. W., and Sijbers, J., “Outlier detection for foot complaint diagnosis: modeling confounding factors using metric learning”, IEEE Intelligent Systems, In Press.
2021
M. Naeyaert, Aelterman, J., Golkov, V., Cremers, D., Pizurica, A., Sijbers, J., and Verhoye, M., “Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing”, Magnetic Resonance in Medicine, vol. 85, no. 3, pp. 1397-1413, 2021.
B. Huyge, Sanctorum, J., Six, N., De Beenhouwer, J., and Sijbers, J., “Analysis of flat fields in edge illumination phase contrast imaging”, in IEEE International Symposium on Biomedical Imaging (ISBI) , 2021.
J. Morez, Sijbers, J., Vanhevel, F., and Jeurissen, B., “Constrained spherical deconvolution of non-spherically sampled diffusion MRI data”, Human Brain Mapping, vol. 42, pp. 521–538, 2021.PDF icon Download paper (5.87 MB)
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Dark field sensitivity in a single mask edge illumination setup”, in IEEE International Symposium on Biomedical Imaging (ISBI) , 2021.
B. De Samber, Renders, J., Elberfeld, T., Maris, Y., Sanctorum, J., Six, N., Liang, Z., De Beenhouwer, J., and Sijbers, J., “FleXCT: a Flexible X-ray CT scanner with 10 degrees of freedom”, Optics Express, vol. 29, no. 3, pp. 3438-3457, 2021.PDF icon Download paper (14.25 MB)
M. Ljubenović, Zhuang, L., De Beenhouwer, J., and Sijbers, J., “Joint Deblurring and Denoising of THz Time-Domain Images”, IEEE Access, vol. 9, pp. 162-176, 2021.PDF icon Download paper (2.38 MB)
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., “Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography”, Measurement Science and Technology, vol. 32, no. 035404, pp. 1-11, 2021.
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.
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, no. 14, 2021.
2020
P. Bladt, “Accurate and precise perfusion parameter estimation in pseudo-continuous arterial spin labeling MRI”, 2020.
P. Paramonov, Lumbeeck, L. - P., De Beenhouwer, J., and Sijbers, J., “Accurate terahertz simulation with ray tracing incorporating beam shape and refraction”, in IEEE ICIP , 2020.PDF icon Download paper (190.62 KB)
D. Frenkel, De Beenhouwer, J., and Sijbers, J., “An adaptive probability map for the Discrete Algebraic Reconstruction Technique”, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
J. Renders, Sijbers, J., and De Beenhouwer, J., “Adjoint pairs of image warping operators for motion modeling in 4D-CT”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (617.11 KB)
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibers”, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.PDF icon Download paper (703.79 KB)
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibres”, Nondestructive Testing and Evaluation, vol. 35, no. 3, pp. 328-341, 2020.
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.
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., “The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling”, NMR in Biomedicine, vol. 33, no. 12, pp. 1-17, 2020.PDF icon Download paper (16.44 MB)
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.
P. Van Dyck, Froeling, M., Heusdens, C. H. W., Sijbers, J., Ribbens, A., and Billiet, T., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study”, Journal of Orthopaedic Research , pp. 1-13, 2020.
P. Van Dyck, Billiet, T., Desbuquoit, D., Verdonk, P., Heusdens, C. H., Roelant, E., Sijbers, J., and Froeling, M., “Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study”, European Radiology, 2020.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model”, Computers in Biology and Medicine, vol. 117, no. 103600, pp. 1-13, 2020.
L. F. Alves Pereira, De Beenhouwer, J., Kastner, J., and Sijbers, J., “Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks”, in ICTAI 2020, 2020.PDF icon Download paper (2.5 MB)

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