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2020
L. F. Alves Pereira, De Beenhouwer, J., Kastner, J., and Sijbers, J., Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks, in ICTAI 2020, 2020.PDF icon Download paper (2.5 MB)
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., Harmonisation of Brain Diffusion MRI: Concepts and Methods, Frontiers in Neuroscience , vol. 14, pp. 1-17, 2020.PDF icon Download paper (2.61 MB)
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., How Hyperspectral Image Unmixing and Denoising Can Boost Each Other, Remote Sensing, vol. 12, no. 1728, 2020.PDF icon remotesensing-12-01728.pdf (2.27 MB)
V. Anania, Billiet, T., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., Improved voxel-wise quantification of diffusion and kurtosis metrics in the presence of noise and intensity outliers, 12th Annual Meeting ISMRM Benelux Chapter, Arnhem, The Netherlands. 2020.
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept, ISMRM-Benelux, vol. 12. 2020.
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept, International Society for Magnetic Resonance in Medicine (ISMRM), vol. 28. 2020.
Q. Beirinckx, Ramos-Llordén, G., Jeurissen, B., Poot, D. H. J., Parizel, P. M., Verhoye, M., Sijbers, J., and den Dekker, A. J., Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study, Fundamenta Informaticae, vol. 172, pp. 105–128, 2020.PDF icon Download paper (final author version) (2.15 MB)
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Momsen, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging, Journal of Nuclear Medicine, vol. 61, p. 573, 2020.PDF icon Download paper (127.73 KB)
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
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.
B. Koirala, Zahiri, Z., and Scheunders, P., A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7393-7405, 2020.PDF icon final_version_leaf_parameter_estimation.pdf (2.66 MB)
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I. B., Manko, O., Danilichev, S., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., Eulenburg, Pzu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., Macro- and microstructural changes in cosmonauts’ brains after long-duration spaceflight, Science Advances, vol. 6, no. 36, p. eaaz9488, 2020.PDF icon Download paper (942.53 KB)
N. Six, Renders, J., Sijbers, J., and De Beenhouwer, J., Newton-Krylov Methods For Polychromatic X-Ray CT, in 2020 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, 2020, pp. 3045-3049.
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.
M. Nicastro, Beirinckx, Q., Bladt, P., Jeurissen, B., Klein, S., Sijbers, J., Poot, D. H. J., and den Dekker, A. J., Optimal design of a T1 super-resolution reconstruction experiment: a simulation study, 12th Annual Meeting of the ISMRM Benelux Chapter. 2020.PDF icon Download abstract (810.88 KB)
J. Morez, Sijbers, J., and Jeurissen, B., Optimal experimental design for multi-tissue spherical deconvolution of diffusion MRI, Proc Intl Soc Mag Reson Med 28. p. 4321, 2020.
B. G. Booth, Hoefnagels, E., Huysmans, T., Sijbers, J., and Keijsers, N. L. W., PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping, PlosOne, vol. 15, no. 2, p. e0229685, 2020.
J. Sanctorum, Nguyen, V., Sijbers, J., Van Wassenbergh, S., and Dirckx, J. J. J., Projection angle adapted distortion correction in high-speed image-intensifier based tomography, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (818.64 KB)
M. Roshani, Phan, G., Faraj, R. Hassan, Phan, N. - H., Roshani, G. Hossein, Corniani, E., and Nazemi, E., Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products, Nuclear Engineering and Technology, 2020.PDF icon 1-s2.0-s1738573320308779-main.pdf (1.38 MB)
L. - P. Lumbeeck, Paramonov, P., Sijbers, J., and De Beenhouwer, J., The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape, in IEEE ICIP, 2020, pp. 3040-3044.PDF icon Download paper (692.64 KB)
B. Auer, Kalluri, K., De Beenhouwer, J., Doty, K., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT, Journal of Nuclear Medicine, vol. 61, p. 103, 2020.PDF icon snm2020_recon_curved.pdf (103.23 KB)
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.PDF icon Download paper (2.49 MB)
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., Ringing Artefact Removal From Sparse View Tomosynthesis using Deep Neural Networks, in The 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 380-383.PDF icon Download paper (570.79 KB)
C. Smekens, Vanhevel, F., Jeurissen, B., Van Dyck, P., Sijbers, J., and Janssens, T., Short T2* quantification of knee structures based on accelerated UTE Spiral VIBE MRI with SPIRiT reconstruction, Proc Intl Soc Mag Reson Med 28. p. 2687, 2020.
C. Smekens, Vanhevel, F., Jeurissen, B., Van Dyck, P., Sijbers, J., and Janssens, T., Short T2* quantification of knee structures based on accelerated UTE Spiral VIBE MRI with SPIRiT reconstruction, 12th Annual Meeting of the ISMRM Benelux Chapter, Arnhem, The Netherlands. 2020.

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