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X-ray imaging

Probability of Detection applied to X-ray inspection using numerical simulations

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.

Evaluation of deeply supervised neural networks for 3D pore segmentation in additive manufacturing

D. Iuso, Chatterjee, S., Heylen, R., Cornelissen, S., De Beenhouwer, J., and Sijbers, J., “Evaluation of deeply supervised neural networks for 3D pore segmentation in additive manufacturing”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122421K.

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Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps

N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122420O.

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.

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