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X-ray imaging
Ring Artifact Reduction in Sinogram Space Using Deep Learning
M. Nauwynck
,
Bazrafkan, S.
,
Van Heteren, A.
,
De Beenhouwer, J.
, and
Sijbers, J.
,
“
Ring Artifact Reduction in Sinogram Space Using Deep Learning
”
, in
6th International Conference on Image Formation in X-Ray Computed Tomography
, 2020.
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Adjoint pairs of image warping operators for motion modeling in 4D-CT
J. Renders
,
Sijbers, J.
, and
De Beenhouwer, J.
,
“
Adjoint pairs of image warping operators for motion modeling in 4D-CT
”
, in
6th International Conference on Image Formation in X-Ray Computed Tomography
, 2020.
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BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration
V. Nguyen
,
De Beenhouwer, J.
,
Bazrafkan, S.
,
Hoang, A. - T.
,
Van Wassenbergh, S.
, and
Sijbers, J.
,
“
BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration
”
, in
6th International Conference on Image Formation in X-Ray Computed Tomography
, 2020, pp. 518-521.
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Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning
T. Van De Looverbosch
,
Bhuiyan, H. Rahman
,
Verboven, P.
,
Dierick, M.
,
Van Loo, D.
,
De Beenhouwer, J.
,
Sijbers, J.
, and
Nicolai, B.
,
“
Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning
”
,
Food Control
, vol. 113, no. 107170, pp. 1-13, 2020.
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Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)
B. De Samber
,
De Rycke, R.
,
De Bruyne, M.
,
Kienhuis, M.
,
Sandblad, L.
,
Bohic, S.
,
Cloetens, P.
,
Urban, C.
,
Polerecky, L.
, and
Vincze, L.
,
“
Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)
”
,
Analytica Chimica Acta
, vol. 1106, pp. 22-32, 2020.
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A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants
B. G. Booth
,
Sijbers, J.
, and
De Beenhouwer, J.
,
“
A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants
”
,
Scientific Reports
, vol. 10, no. 661, 2020.
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Tomography for in-line product inspection
T. De Schryver
,
Dierick, M.
,
Van Hoorebeke, L.
,
Verboven, P.
,
Van Dael, M.
, and
Sijbers, J.
,
“
Tomography for in-line product inspection
”
, U.S. Patent EP3106863A12015.
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An adaptive probability map for the Discrete Algebraic Reconstruction Technique
D. Frenkel
,
De Beenhouwer, J.
, and
Sijbers, J.
,
“
An adaptive probability map for the Discrete Algebraic Reconstruction Technique
”
, in
10th Conference on Industrial Computed Tomography (ICT 2020)
, 2020, pp. 1-6.
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Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT
A. Presenti
,
Bazrafkan, S.
,
Sijbers, J.
, and
De Beenhouwer, J.
,
“
Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT
”
, in
10th Conference on Industrial Computed Tomography (ICT 2020)
, 2020.
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poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT
N. Six
,
De Beenhouwer, J.
, and
Sijbers, J.
,
“
poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT
”
,
Optics Express
, vol. 27, no. 23, pp. 33427-33435, 2019.
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