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Presenti, A., S. Bazrafkan, J. Sijbers, and J. De Beenhouwer, "Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT", 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
Van Houtte, J., S. Bazrafkan, F. Vandenberghe, G. Zheng, and J. Sijbers, "A Deep Learning Approach to Horse Bone Segmentation from Digitally Reconstructed Radiographs", International Conference on Image Processing Theory, Tools, and Applications, 2019.
Sabidussi, E. Ribeiro, M. Nicastro, S. Bazrafkan, Q. Beirinckx, B. Jeurissen, A J. den Dekker, S. Klein, and D. H. J. Poot, "A deep learning approach to T1 mapping in quantitative MRI", 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands, vol. 32 (Suppl. 1), no. S09.05: Magn Reson Mater Phy, 2019.
Rimpelainen, J., S. Bazrafkan, J. Sijbers, and J. De Beenhouwer, "Deep learning based missing wedge artefact removal for electron tomography", Microscopy Conference, Berlin, Germany, pp. 660-661, 2019.
Elberfeld, T., S. Bazrafkan, J. De Beenhouwer, and J. Sijbers, "Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images", 4th International Conference on Tomography of Materials & Structures, 07/2019.