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D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, vol. 54, pp. 13160–13177, 2024.PDF icon Download paper (2.48 MB)
D. Iuso, Paramonov, P., De Beenhouwer, J., and Sijbers, J., “Practical multi-mesh registration for few-view poly-chromatic X-ray inspection”, Journal of Non-destructive Testing, vol. 43, 2024.PDF icon Download paper (6.94 MB)
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.PDF icon Download paper (protected) (1.79 MB)
D. Iuso, Nazemi, E., Six, N., De Samber, B., De Beenhouwer, J., and Sijbers, J., “CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts”, in IEEE ICIP, 2021, pp. 2948-2952.
D. Iuso, Paramonov, P., De Beenhouwer, J., and Sijbers, J., “PACS: Projection-driven with Adaptive CADs X-ray Scatter compensation for additive manufacturing inspection”, Precision Engineering, vol. 90, pp. 108-121, 2024.PDF icon Download paper (4.28 MB)