Publications

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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, pp. 3035-3039.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, pp. 1-6.
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 Fibres, Nondestructive Testing and Evaluation, vol. 35, no. 3, pp. 328-341, 2020.
B. Auer, Kalluri, K., Abayazeed, A. H., De Beenhouwer, J., Zeraatkar, N., Lindsay, C., Momsen, N., R. Richards, G., May, M., Kupinski, M. A., Kuo, P. H., Furenlid, L. R., and King, M. A., Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020), 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)
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.
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)
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Momsen, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging, Journal of Nuclear Medicine, vol. 61, p. 573, 2020.PDF icon Download paper (127.73 KB)
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
B. G. Booth, Sijbers, J., and De Beenhouwer, J., A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants, Scientific Reports, vol. 10, no. 661, 2020.
N. Six, Renders, J., Sijbers, J., and De Beenhouwer, J., Newton-Krylov Methods For Polychromatic X-Ray CT, in 2020 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, 2020, pp. 3045-3049.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
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)
B. Auer, Kalluri, K., De Beenhouwer, J., Doty, K., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT, Journal of Nuclear Medicine, vol. 61, p. 103, 2020.PDF icon snm2020_recon_curved.pdf (103.23 KB)
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)
J. Sanctorum, De Beenhouwer, J., and Sijbers, J., X-ray phase contrast simulation for grating-based interferometry using GATE, Optics Express, vol. 28, no. 22, pp. 33390-33412, 2020.PDF icon Download paper (2.5 MB)
2019
A. Presenti, Sijbers, J., den Dekker, A. J., and De Beenhouwer, J., CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019, pp. 1-5.PDF icon ict2019_full_paper_55.pdf (216.2 KB)
J. Rimpelainen, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., Deep learning based missing wedge artefact removal for electron tomography, Microscopy Conference, Berlin, Germany. pp. 660-661, 2019.
A. Presenti, Sijbers, J., and De Beenhouwer, J., Dynamic angle selection for few-view X-ray inspection of CAD based objects, in Proc. SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.
E. Janssens, Sijbers, J., Dierick, M., and De Beenhouwer, J., Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.
T. Elberfeld, De Beenhouwer, J., and Sijbers, J., Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.PDF icon Download paper (5.15 MB)

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