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X-ray imaging

Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography

A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography”, in e-Journal of Nondestructive Testing, 2022, vol. 27 (3), pp. 1-5.

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Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique

J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., “Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique”, Physics in Medicine and Biology, vol. 66, no. 16, 2021.

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Motion compensating X-ray micro-CT of diamonds in a processing stage

J. Renders, Nguyen, A. - T., De Beenhouwer, J., and Sijbers, J., “Motion compensating X-ray micro-CT of diamonds in a processing stage”, 31st International Conference on Diamond and Carbon Materials. 2021.

2D/3D registration with a statistical deformation model prior using deep learning

J. Van Houtte, Gao, X., Sijbers, J., and Zheng, G., “2D/3D registration with a statistical deformation model prior using deep learning”, in the IEEE International Conference on Biomedical and Health Informatics (BHI'21) , 2021.

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CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts

D. Iuso, Nazemi, E., Six, N., De Samber, B., De Beenhouwer, J., and Sijbers, J., “CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts”, in IEEE ICIP, 2021.

Dynamic few-view X-ray imaging for inspection of CAD-based objects

A. Presenti, Sijbers, J., and De Beenhouwer, J., “Dynamic few-view X-ray imaging for inspection of CAD-based objects”, Expert Systems with Applications, vol. 180, p. 115012, 2021.

Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning

T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., “Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning”, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 2021.

Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction

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.

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A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis

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.

Tabu-DART: an dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search

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.

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