Publications

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Journal Article
V. Van Nieuwenhove, Van Eyndhoven, G., Batenburg, K. J., Buls, N., Vandemeulebroucke, J., De Beenhouwer, J., and Sijbers, J., “Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT”, Medical Physics, vol. 43, no. 12, pp. 6429-6438, 2016.
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.
B. Goris, De Beenhouwer, J., De Backer, A., Zanaga, D., Batenburg, K. J., Sánchez-Iglesias, A., Liz-Marzán, L. M., Van Aert, S., Bals, S., Sijbers, J., and Van Tendeloo, G., “Measuring Lattice Strain in Three Dimensions through Electron Microscopy”, Nano Letters, vol. 15, no. 10, pp. 6996–7001, 2015.
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)
V. Van Nieuwenhove, De Beenhouwer, J., Vlassenbroeck, J., Brennan, M., and Sijbers, J., “MoVIT: A tomographic reconstruction framework for 4D-CT”, Optics Express, vol. 25, no. 16, pp. 19236-19250, 2017.
E. Janssens, De Beenhouwer, J., Van Dael, M., De Schryver, T., Van Hoorebeke, L., Verboven, P., Nicolai, B., and Sijbers, J., “Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection”, Measurement Science and Technology, vol. 29, no. 3, 2018.PDF icon Download paper (3.4 MB)
H. K. Jenssen, Oberlander, B. C., De Beenhouwer, J., Sijbers, J., and Verwerft, M., “Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor”, Progress in Nuclear Energy, vol. 72, pp. 55-62, 2014.
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.
D. Iuso, Paramonov, P., De Beenhouwer, J., and Sijbers, J., “PACS: Projection-driven with Adaptive CADs X-ray Scatter compensation for additive manufacturing inspection”, Precision Engineering, vol. 90, pp. 108-121, 2024.PDF icon Download paper (4.28 MB)
T. Elberfeld, De Beenhouwer, J., den Dekker, A. J., Heinzl, C., and Sijbers, J., “Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study”, Journal of Nondestructive Evaluation, vol. 37, no. 62, pp. 1573-4862, 2018.
N. Six, De Beenhouwer, J., and Sijbers, J., “poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT”, Optics Express, vol. 27, no. 23, pp. 33427-33435, 2019.PDF icon Download paper (997.08 KB)
D. Iuso, Paramonov, P., De Beenhouwer, J., and Sijbers, J., “Practical multi-mesh registration for few-view poly-chromatic X-ray inspection”, Journal of Non-destructive Testing, vol. 43, 2024.PDF icon Download paper (6.94 MB)
A. Könik, Auer, B., De Beenhouwer, J., Kalluri, K., Zeraatkar, N., Furenlid, L. R., and King, M. A., “Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT”, Physics in Medicine & Biology, vol. 64, no. 24, p. 245001, 2019.PDF icon i123_spectra_final_revision_11_7_19.pdf (7.63 MB)
M. Yosifov, Reiter, M., Heupl, S., Gusenbauer, C., Fröhler, B., R. Gutierrez, F. -, De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Probability of Detection applied to X-ray inspection using numerical simulations”, Nondestructive Testing and Evaluation, vol. 37, no. 5, pp. 536-551, 2022.
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.
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)
A. Könik, De Beenhouwer, J., Mukherjee, J. M., Kalluri, K., Banerjee, S., Zeraatkar, N., Fromme, T. J., and King, M. A., “Simulations of a Multipinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging”, IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 2, pp. 444-451, 2018.
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., “The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?”, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
D. Frenkel, Six, N., De Beenhouwer, J., and Sijbers, J., “Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction”, The Visual Computer, vol. 39, pp. 4671–4683, 2023.PDF icon Download paper (2.31 MB)
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.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., “A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science”, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, vol. 54, pp. 13160–13177, 2024.PDF icon Download paper (2.48 MB)
B. Huyge, Renders, J., Sanctorum, J., De Beenhouwer, J., and Sijbers, J., “X-ray image reconstruction for continuous acquisitions with a generalized motion model”, Optics Express, vol. 32, no. 22, pp. 39192-39207, 2024.

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