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2022
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)
B. Huyge, Jeurissen, B., De Beenhouwer, J., and Sijbers, J., “Fiber orientation estimation by constrained spherical deconvolution of the anisotropic edge illumination x-ray dark field signal”, in SPIE: Developments in X-Ray Tomography XIV, 2022, vol. 12242, p. 122420V .PDF icon Download paper (956.82 KB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., “Hyperspectral clustering using atrous spatial-spectral convolutional network”, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122420O.
C. Bossuyt, De Beenhouwer, J., and Sijbers, J., “Optimization of a multi-source rectangular X-ray CT geometry for inline inspection”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 1224219 .
B. Koirala and Scheunders, P., “A robust supervised method to estimate chlorophyll ab content from spectral reflectance”, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
B. Koirala and Scheunders, P., “A Robust Supervised Method to Estimate Chlorophyll Ab Content from Spectral Reflectance”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 326-329.PDF icon igarss_2022.pdf (238.85 KB)
B. Rasti, Koirala, B., and Scheunders, P., “Sparse Unmixing using Deep Convolutional Networks”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 24-27.PDF icon suncnn_igarss2022.pdf (1.03 MB)
B. Rasti, Koirala, B., and Scheunders, P., “Sparse unmixing using deep convolutional networks”, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
2021
J. Van Houtte, Gao, X., Sijbers, J., and Zheng, G., “2D/3D registration with a statistical deformation model prior using deep learning”, in the IEEE International Conference on Biomedical and Health Informatics (BHI'21) , 2021, pp. 1-4.PDF icon Download paper (1.41 MB)
L. - P. Lumbeeck, Paramonov, P., Sijbers, J., and De Beenhouwer, J., “3D THz Tomography Incorporating the Beam Shape”, in 2021 OSA Imaging and Applied Optics Congress, 2021.
B. Huyge, Sanctorum, J., Six, N., De Beenhouwer, J., and Sijbers, J., “Analysis of flat fields in edge illumination phase contrast imaging”, in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 2021, pp. 1310-1313.PDF icon Download paper (368.24 KB)
B. Rasti, Koirala, B., Scheunders, P., Ghamisi, P., and Gloaguen, R., “Boosting Hyperspectral Image Unmixing using Denoising: Four Scenarios”, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
B. Rasti, Koirala, B., Scheunders, P., Ghamisi, P., and Gloaguen, R., “BOOSTING HYPERSPECTRAL IMAGE UNMIXING USING DENOISING: FOUR SCENARIOS”, in IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021.
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.
A. Presenti, Liang, Z., Alves Pereira, L. F., Sijbers, J., and De Beenhouwer, J., “CNN-based Pose Estimation of Manufactured Objects During Inline X-ray Inspection”, in 2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), 2021.
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Dark field sensitivity in single mask edge illumination lung imaging”, in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 2021, pp. 775-778.
L. F. Alves Pereira, Van Nieuwenhove, V., De Beenhouwer, J., and Sijbers, J., “A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
T. Hu, Liu, N., Li, W., Tao, R., Zhang, F., and Scheunders, P., “Destriping Hyperspectral Imagery By Adaptive Anisotropic Total Variation And Truncated Nuclear Norm”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
J. Van Houtte, Sijbers, J., and Zheng, G., “Graphical User Interface for Joint Space Width Assessment by Optical Marker Tracking”, in 4th International Conference on Bio-engineering for Smart Technologies, 2021.
J. Renders, De Beenhouwer, J., and Sijbers, J., “Mesh-based reconstruction of dynamic foam images using X-ray CT”, in International Conference on 3D Vision (3DV2021), 2021, pp. 1312-1320.
B. Shafieizargar, Jeurissen, B., Poot, D. H. J., den Dekker, A. J., and Sijbers, J., “Multi-contrast multi-shot EPI for accelerated diffusion MRI”, in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021, pp. 3869-3872.
K. Rafiezadeh Sahi, Ghamisi, P., Jackisch, R., Rasti, B., Scheunders, P., and Gloaguen, R., “A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
E. Ribeiro Sabidussi, Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as Inverse Problem Solvers for MR Relaxometry”, in MIDL 2021 - Medical Imaging with Deep Learning, 2021.

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