Publications

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In Press
J. Renders, Sijbers, J., and De Beenhouwer, J., “Adjoint image warping using multivariate splines with application to 4D-CT”, Medical Physics, In Press.
A. Presenti, Sijbers, J., and De Beenhouwer, J., “Dynamic few-view X-ray imaging for inspection of CAD-based objects Expert Systems With Applications”, Expert Systems with Applications , In Press.
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) , Nice, France, 2021.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Dark field sensitivity in single mask edge illumination lung imaging”, in IEEE International Symposium on Biomedical Imaging (ISBI) , Nice, France, 2021.
L. F. Alves Pereira, Van Nieuwenhove, V., De Beenhouwer, J., and Sijbers, J., “A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis ”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 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)
V. Nguyen, Sanctorum, J., Van Wassenbergh, S., Dirckx, J. J. J., Sijbers, J., and De Beenhouwer, J., “Geometry Calibration of a Modular Stereo Cone-Beam X-ray CT System”, Journal of Imaging, vol. 7, no. 54, pp. 1-12, 2021.PDF icon Download paper (4.2 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)
E. Nazemi, Six, N., Iuso, D., De Samber, B., Sijbers, J., and De Beenhouwer, J., “Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction”, Applied Sciences, vol. 11, no. 7, 2021.PDF icon Download paper (4.96 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.
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.
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. 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.
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.

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