Publications

Export 1297 results:
Author Type [ Year(Asc)]
2021
B. G. Booth, Keijsers, N. L. W., and Sijbers, J., Outlier detection for foot complaint diagnosis: modeling confounding factors using metric learning, IEEE Intelligent Systems, vol. 36, no. 3, pp. 41-49, 2021.
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography, Measurement Science and Technology, vol. 32, no. 035404, pp. 1-11, 2021.
D. Giraldo, Sijbers, J., and Romero, E., Quantification of cognitive impairment to characterize heterogeneity of patients at risk of developing Alzheimer's disease dementia, Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, vol. 13, no. 1, p. e12237, 2021.
M. A. Zampini, Sijbers, J., Verhoye, M., and Garipov, R., RAMSES: Relaxation Alternate Mapping of Spoiled Echo Signals sequence for simultaneous accurate T1 and T2* mapping, ISMRM & SMRT Annual Meeting. 2021.
E. Ribeiro Sabidussi, Klein, S., 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, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
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.
B. Koirala, Zahiri, Z., Lamberti, A., and Scheunders, P., Robust supervised method for nonlinear spectral unmixing accounting for endmember variability, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7434-7448, 2021.PDF icon ieee_version.pdf (3.76 MB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer, Magn Reson Mater Phy (ESMRMB), vol. 34. pp. S56-S57, 2021.
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., Spectral Unmixing Using Deep Convolutional Encoder-Decoder, in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 3829-3832.PDF icon igarss2021.pdf (659.27 KB)
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., Spectral Unmixing Using Deep Convolutional Encoder-Decoder, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
F. Danckaers, Van Houtte, J., Booth, B. G., Verstreken, F., and Sijbers, J., Statistical shape and pose model of the forearm for custom splint design, in IEEE International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1669-1672.PDF icon Download paper (1.54 MB)
M. Naeyaert, Strategies for efficient acquisition and reconstruction of structural and quantitative MRI, 2021.
P. Paramonov, Lumbeeck, L. - P., Sijbers, J., and De Beenhouwer, J., A study of terahertz beam simulation with ray tracing for computed tomography, in 2021 OSA Imaging and Applied Optics Congress, 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.
2020
S. Van Aert, De Backer, A., De wael, A., Fatermans, J., Friedrich, T., Lobato, I., O'Leary, C. M., Varambhia, A., Altantzis, T., Jones, L., den Dekker, A. J., Nellist, P. D., and Bals, S., 3D Atomic Scale Quantification of Nanostructures and their Dynamics Using Model-based STEM, Microscopy & Microanalysis 2020 (online), Milwaukee, United States. 2020.
P. Bladt, Accurate and precise perfusion parameter estimation in pseudo-continuous arterial spin labeling MRI, 2020.
P. Paramonov, Lumbeeck, L. - P., De Beenhouwer, J., and Sijbers, J., Accurate terahertz simulation with ray tracing incorporating beam shape and refraction, in IEEE ICIP , 2020, pp. 3035-3039.PDF icon Download paper (190.62 KB)
D. Frenkel, De Beenhouwer, J., and Sijbers, J., An adaptive probability map for the Discrete Algebraic Reconstruction Technique, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020, pp. 1-6.
J. Renders, Sijbers, J., and De Beenhouwer, J., Adjoint pairs of image warping operators for motion modeling in 4D-CT, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (617.11 KB)
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibres, Nondestructive Testing and Evaluation, vol. 35, no. 3, pp. 328-341, 2020.

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