Tomography

Tomography is an imaging technique that combines projections taken from different directions into a reconstruction of the interior of a patient or an object. The ASTRA research group (“All Scales Tomographic Reconstruction Antwerp”) of imec-Vision Lab develops tomographic reconstruction algorithms for electron, X-ray, neutron, and magnetic resonance imaging. The ASTRA group developed the ASTRA-Toolbox, which is an open source, GPU accelerated software platform for the development of novel tomographic reconstruction methods; it can be downloaded from www.astra-toolbox.com.

Key expertises:

  • Phase contrast X-ray CT (edge illumination and grating based interferometry)
  • X-ray tomography for non-standard acquisition geometries (e.g. laminography, tomosynthesis, ...)
  • Dynamic (4D) tomography
  • Discrete tomography
  • Electron tomography

Journal publications

2023

M. Vandecasteele, Heylen, R., Iuso, D., Thanki, A., Philips, W., Witvrouw, A., Verhees, D., and Booth, B. G., “Towards material and process agnostic features for the classification of pore types in metal additive manufacturing”, Materials & Design, vol. 227, p. 111757, 2023.

2022

A. Presenti, “3D X-ray radiography-based inspection of manufactured objects”, 2022.
V. Nguyen, “Advances in biplanar X-ray imaging: calibration and 2D/3D registration”, 2022.PDF icon Download PhD thesis (8.02 MB)
T. Elberfeld, Fröhler, B., Heinzl, C., Sijbers, J., and De Beenhouwer, J., “cuPARE: Parametric Reconstruction of Curved Fibres from Glass fibre-reinforced Composites”, Nondestructive Testing and Evaluation, 2022.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)
D. Frenkel, Six, N., De Beenhouwer, J., and Sijbers, J., “Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction”, The Visual Computer, vol. 438, no. 1, 2022.PDF icon Download paper (2.31 MB)
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.
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.
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.

2021

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.

Pages