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2021
M. Ljubenović, Zhuang, L., De Beenhouwer, J., and Sijbers, J., “Joint Deblurring and Denoising of THz Time-Domain Images”, IEEE Access, vol. 9, pp. 162-176, 2021.PDF icon Download paper (2.38 MB)
E. Nazemi, Six, N., Iuso, D., De Samber, B., Sijbers, J., and De Beenhouwer, J., “Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction”, Applied Sciences, vol. 11, no. 7, 2021.PDF icon Download paper (4.96 MB)
B. Jeurissen and Szczepankiewicz, F., “Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.”, Neuroimage, vol. 245, p. 118717, 2021.
T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., “Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning”, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 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.
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)
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)
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)
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)
2020
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.
M. Roshani, Sattari, M. Amir, Ali, P. Jammal Muh, Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter”, Flow Measurement and Instrumentation, vol. 75, 2020.
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Gauquelin, N., Verbeeck, J., and Van Aert, S., “Atom column detection from simultaneously acquired ABF and ADF STEM images”, Ultramicroscopy, vol. 219, p. 113046, 2020.
J. Morez, Sijbers, J., Vanhevel, F., and Jeurissen, B., “Constrained spherical deconvolution of non-spherically sampled diffusion MRI data”, Human Brain Mapping, vol. 42, pp. 521–538, 2020.PDF icon Download paper (5.87 MB)
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., “The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling”, NMR in Biomedicine, vol. 33, no. 12, pp. 1-17, 2020.PDF icon Download paper (16.44 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P., and Gloaguen, R., “Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm”, Remote Sensing, vol. 12 (23), no. 4007, 2020.PDF icon remotesensing-12-04007-v2.pdf (21.88 MB)
V. Varkarakis, Bazrafkan, S., and Corcoran, P., “Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets”, Science Direct Elsevier Neural Networks, vol. 121, pp. 101-121, 2020.
P. Van Dyck, Billiet, T., Desbuquoit, D., Verdonk, P., Heusdens, C. H., Roelant, E., Sijbers, J., and Froeling, M., “Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study”, European Radiology, vol. 34, pp. 6673–6684, 2020.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model”, Computers in Biology and Medicine, vol. 117, no. 103600, pp. 1-13, 2020.
B. De Samber, De Rycke, R., De Bruyne, M., Kienhuis, M., Sandblad, L., Bohic, S., Cloetens, P., Urban, C., Polerecky, L., and Vincze, L., “Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)”, Analytica Chimica Acta, vol. 1106, pp. 22-32, 2020.PDF icon Download paper (4.01 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)
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)

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