Publications

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Conference Paper
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.
E. Janssens, De Beenhouwer, J., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., “Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt”, in IEEE International Conference on Image Processing, 2015, pp. 917-921.
J. Renders, De Beenhouwer, J., and Sijbers, J., “Mesh-based reconstruction of dynamic foam images using X-ray CT”, in International Conference on 3D Vision (3DV2021), 2021, pp. 1312-1320.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., “A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122420O.
N. Six, De Beenhouwer, J., Van Nieuwenhove, V., Vanroose, W., and Sijbers, J., “Joint reconstruction and flat-field estimation using support estimation”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.PDF icon Download paper (1.53 MB)
K. Zarei Zefreh, De Beenhouwer, J., Welford, F. M., and Sijbers, J., “Investigation on Effect of scintillator thickness on Afterglow in Indirect X-ray Detectors”, in 6th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2016), 2016.
B. Auer, Zeraatkar, N., De Beenhouwer, J., Kalluri, K., Kuo, P. H., Furenlid, L. R., and King, M. A., “Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging”, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, vol. 11072, pp. 187 – 190.
J. Weissenböck, Fröhler, B., Gröller, E., Sanctorum, J., De Beenhouwer, J., Sijbers, J., Karunakaran, S. Ayalur, Hoeller, H., Kastner, J., and Heinzl, C., “An Interactive Visual Comparison Tool for 3D Volume Datasets represented by Nonlinearly Scaled 1D Line Plots through Space-filling Curves”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.22 MB)
B. Huyge, Jeurissen, B., De Beenhouwer, J., and Sijbers, J., “Fiber orientation estimation by constrained spherical deconvolution of the anisotropic edge illumination x-ray dark field signal”, in SPIE: Developments in X-Ray Tomography XIV, 2022, vol. 12242, p. 122420V .PDF icon Download paper (956.82 KB)
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)
E. Janssens, Senck, S., Heinzl, C., Kastner, J., De Beenhouwer, J., and Sijbers, J., “Fast Reconstruction of CFRP X-ray Images based on a Neural Network Filtered Backprojection Approach”, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (345.06 KB)
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.
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)
D. Iuso, Chatterjee, S., Heylen, R., Cornelissen, S., De Beenhouwer, J., and Sijbers, J., “Evaluation of deeply supervised neural networks for 3D pore segmentation in additive manufacturing”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122421K.PDF icon Download paper (protected) (1.79 MB)
N. Francken, Paramonov, P., Sijbers, J., and De Beenhouwer, J., “Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations”, in IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy, 2023.PDF icon eurocon_2023.pdf (8.52 MB)
P. Paramonov, Renders, J., Elberfeld, T., De Beenhouwer, J., and Sijbers, J., “Efficient X-ray projection of triangular meshes based on ray tracing and rasterization”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122420W .PDF icon Download paper (1.72 MB)
Á. Marinovszki, De Beenhouwer, J., and Sijbers, J., “An efficient CAD projector for X-ray projection based 3D inspection with the ASTRA Toolbox”, in 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018.PDF icon Download paper (364.16 KB)
G. Van Eyndhoven, De Beenhouwer, J., and Sijbers, J., “A dynamic region estimation method for cerebral perfusion CT”, in 6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS), 2016, pp. 331-342.PDF icon Download paper (840.01 KB)
V. Van Nieuwenhove, De Beenhouwer, J., and Sijbers, J., “Dynamic flat field correction in X-ray computed tomography”, in Optimess conference, 2016, Antwerp.
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.
W. Van Aarle, Cant, J., De Beenhouwer, J., and Sijbers, J., “Discrete tomographic reconstruction from deliberately motion blurred X-ray projections”, in 6th Conference on Industrial Computed Tomography, Wels, Austria, 2016, pp. 1-6.PDF icon Download paper (444.66 KB)
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.
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.
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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