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X-ray imaging

Optimization of a multi-source rectangular X-ray CT geometry for inline inspection

C. Bossuyt, De Beenhouwer, J., and Sijbers, J., “Optimization of a multi-source rectangular X-ray CT geometry for inline inspection”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 1224219 .

Efficient X-ray projection of triangular meshes based on ray tracing and rasterization

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 .

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An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography

A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F, San Diego, CA, United States, 2022.

Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?

J. Sanctorum, Six, N., Sijbers, J., and De Beenhouwer, J., “Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, San Diego, USA, 2022, p. 1224218.

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Automatic anomaly detection from X-ray images based on autoencoder

A. Presenti, Liang, Z., Alves Pereira, L. F., Sijbers, J., and De Beenhouwer, J., “Automatic anomaly detection from X-ray images based on autoencoder”, Nondestructive Testing and Evaluation, vol. 37, no. 5, 2022.

Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images

T. Van De Looverbosch, Jiaqi, H., Tempelaere, A., Kelchtermans, K., Verboven, P., Tuytelaars, T., Sijbers, J., and Nicolai, B., “Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images”, Computers and Electronics in Agriculture, vol. 197, no. 106962, pp. 1-14, 2022.

Sparse view rectangular X-ray CT for cargo inspection using the ASTRA toolbox

C. Bossuyt, De Beenhouwer, J., and Sijbers, J., “Sparse view rectangular X-ray CT for cargo inspection using the ASTRA toolbox”, 5th international Conference on Tomography of Materials & Structures, 27the June - 1ste July, Grenoble, France. 2022.

Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images

J. Van Houtte, Audenaert, E., Zheng, G., and Sijbers, J., “Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images”, International Journal of Computer Assisted Radiology and Surgery, vol. 309, pp. 1333–1342, 2022.

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3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts

R. Heylen, Thanki, A., Verhees, D., Iuso, D., De Beenhouwer, J., Sijbers, J., Witvrouw, A., Haitjema, H., and Bey-Temsamani, A., “3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts”, Measurement Science and Technology, vol. 33, no. 4, pp. 1-12, 2022.

Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images

N. Six, Renders, J., Sijbers, J., and De Beenhouwer, J., “Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images”, IEEE Transactions on Computational Imaging, vol. 7, pp. 1304-1313, 2021.

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