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2021
B. Rasti and Koirala, B., “SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network”, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2021.PDF icon ieee_grsl_sundip.pdf (2.34 MB)
C. Smekens, Beirinckx, Q., Vanhevel, F., Van Dyck, P., den Dekker, A. J., Sijbers, J., Janssens, T., and Jeurissen, B., “Super-resolution T2* mapping of the knee using UTE Spiral VIBE MRI”, Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), 29th Annual Meeting, An Online Experience. p. 3920, 2021.
D. Frenkel, De Beenhouwer, J., and Sijbers, J., “Tabu-DART: an dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., “To Recurse or not to Recurse A Low Dose CT Study”, Progress in Artificial Intelligence, vol. 10, pp. 65–81, 2021.
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., “UnDIP: hyperspectral unmixing using deep image prior”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2021.PDF icon manuscript.pdf (13 MB)
K. Rafiezadeh Sahi, Rasti, B., Ghamisi, P., Scheunders, P., and Gloaguen, R., “When is the right time to apply denoising?”, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
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.
A. Presenti, “3D X-ray radiography-based inspection of manufactured objects”, 2022.
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F, San Diego, CA, United States, 2022.
J. Merckx, van Lith, B., Sijbers, J., and De Beenhouwer, J., “Adaptive triangular mesh for phase contrast imaging”, 5th international Conference on Tomography of Materials & Structures, 27the June - 1ste July, Grenoble, France. 2022.
V. Nguyen, “Advances in biplanar X-ray imaging: calibration and 2D/3D registration”, 2022.PDF icon Download PhD thesis (8.02 MB)
P. - J. Vanthienen, Sanctorum, J., Huyge, B., Six, N., Sijbers, J., and De Beenhouwer, J., “Alternative grating designs for cone-beam edge illumination X-ray phase contrast imaging”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, San Diego, USA, 2022, vol. 12242, p. 122420Z.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., and Scheunders, P., “Analysis of Plant Stress Response Using Hyperspectral Imaging and Kernel Ridge Regression”, in 11th International Conference on Robotics, Vision, Signal Processing and Power Applications, Singapore, 2022, vol. 829.
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography”, in e-Journal of Nondestructive Testing, 2022, vol. 27 (3), pp. 1-5.
J. Sanctorum, Six, N., Sijbers, J., and De Beenhouwer, J., “Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, San Diego, USA, 2022, p. 1224218.PDF icon Download paper (303.24 KB)
P. Lopes, Van Herck, P., Ooms, J., Van Mieghem, N., Wirix-Speetjens, R., Sijbers, J., Vander Sloten, J., and Bosmans, J., “Automated Mitral Valve Assessment for Transcatheter Mitral Valve Replacement (TMVR) Planning”, Frontiers in Bioengineering and Biotechnology, vol. 16, pp. 1-13, 2022.PDF icon Download paper (2.19 MB)
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.
V. Nguyen, Alves Pereira, L. F., Liang, Z., Mielke, F., Van Houtte, J., Sijbers, J., and De Beenhouwer, J., “Automatic landmark detection and mapping for 2D/3D registration with BoneNet”, Frontiers Veterinary Science, 2022.PDF icon Download paper (2.51 MB)
B. Rasti and Koirala, B., “Blind Nonlinear Unmixing For Intimate Mixtures Using Hapke Model And CNN”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022, pp. 1-5.PDF icon whispers_2022_hapkecnn.pdf (1.93 MB)
Y. - T. Ling, Cools, S., Bogdanowicz, J., Fleischmann, C., De Beenhouwer, J., Sijbers, J., and Vandervorst, W., “A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography”, Microscopy and Microanalysis, vol. 28, no. 4, pp. 1-14, 2022.
A. Doroshin, Jillings, S., Jeurissen, B., Tomilovskaya, E., Pechenkova, E. V., Nosikova, I., Rumshiskaya, A., Litvinova, L., Rukavishnikov, I., De Laet, C., Schoenmaekers, C., Sijbers, J., Laureys, S. S. L., Petrovichev, V., Van Ombergen, A., Annen, J., Sunaert, S., Parizel, P. M., Sinitsyn, V., Eulenburg, Pzu, Osipowicz, K., and Wuyts, F. L., “Brain Connectometry Changes in Space Travelers After Long-Duration Spaceflight”, Front. Neural Circuits, vol. 16, 2022.
A. Presenti, Liang, Z., Alves Pereira, L. F., Sijbers, J., and De Beenhouwer, J., “CNN-based pose estimation from a single X-ray projection for 3D inspection of manufactured objects”, in 11th Conference on Industrial Computed Tomography, 2022.
D. Giraldo, “Computational anatomy strategies for characterization of brain patterns associated with Alzheimer's disease”, 2022.PDF icon Download PhD thesis (25.92 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.PDF icon Download paper (9.66 MB)
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., “Deep Blind Unmixing using Minimum Simplex Convolutional Network”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 28-31.PDF icon misicnet_igarss2022.pdf (1.29 MB)

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