Log in

X-ray imaging

Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps

N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps”, Optics Express, In Press.

ImWIP: open-source image warping toolbox with adjoints and derivatives

J. Renders, Jeurissen, B., Nguyen, A. - T., De Beenhouwer, J., and Sijbers, J., “ImWIP: open-source image warping toolbox with adjoints and derivatives”, SoftwareX, vol. 24, p. 101524, 2023.

Grating designs for cone beam edge illumination X-ray phase contrast imaging: a simulation study

P. - J. Vanthienen, Sanctorum, J., Huyge, B., Six, N., Sijbers, J., and De Beenhouwer, J., “Grating designs for cone beam edge illumination X-ray phase contrast imaging: a simulation study”, Optics Express, vol. 31, no. 17, pp. 28051-28064, 2023.

Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution

B. Huyge, Sanctorum, J., Jeurissen, B., De Beenhouwer, J., and Sijbers, J., “Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution”, Polymers, vol. 15, no. 13, p. 2887, 2023.

Files:

Adapting an XCT-scanner to enable edge illumination X-ray phase contrast imaging

B. Huyge, Vanthienen, P. - J., Six, N., Sijbers, J., and De Beenhouwer, J., “Adapting an XCT-scanner to enable edge illumination X-ray phase contrast imaging”, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.

Toward denoising of 3D CT scans with few data

Z. Liang, Van Heteren, A., Sijbers, J., and De Beenhouwer, J., “Toward denoising of 3D CT scans with few data”, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.

Files:

Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations

M. Yosifov, Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations”, e-Journal of Nondestructive Testing, vol. 28, no. 3, 2023.

Files:

The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis

L. F. Alves Pereira, De Beenhouwer, J., and Sijbers, J., “The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis”, in 31st European Signal Processing Conference, EUSIPCO, 2023.

Parametric Fiber Analysis for Glass Fiber-reinforced Composite Tomographic Images

T. Elberfeld, “Parametric Fiber Analysis for Glass Fiber-reinforced Composite Tomographic Images”, 2023.

Files:

Download PhD thesis

A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations

N. Francken, Sanctorum, J., Renders, J., Paramonov, P., Sijbers, J., and De Beenhouwer, J., “A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations”, in 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023.

Files:

Pages