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Tomography

Computed tomography (CT)

A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system

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 , In Press.

Accurate terahertz simulation with ray tracing incorporating beam shape and refraction

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.

Projection angle adapted distortion correction in high-speed image-intensifier based tomography

J. Sanctorum, Nguyen, V., Sijbers, J., Van Wassenbergh, S., and Dirckx, J. J. J., “Projection angle adapted distortion correction in high-speed image-intensifier based tomography”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.

Mobile imaging of an object using penetrating radiation

J. Sijbers and De Beenhouwer, J., “Mobile imaging of an object using penetrating radiation”, U.S. Patent WO/2017/1783342017.

Ring Artifact Reduction in Sinogram Space Using Deep Learning

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.

BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration

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.

Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning

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.

Tomography for in-line product inspection

T. De Schryver, Dierick, M., Van Hoorebeke, L., Verboven, P., Van Dael, M., and Sijbers, J., “Tomography for in-line product inspection”, U.S. Patent EP3106863A12015.

Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging

B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Könik, A., Kuo, P. H., Furenlid, L. R., and King, M. A., “Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging”, 2nd International Conference on Monte Carlo Techniques for Medical Applications. 2019.

Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging

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.

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