Publications

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2022
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Bikram, K., and Scheunders, P., “Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress”, Computers and Electronics in Agriculture, vol. 195, p. 106806, 2022.PDF icon non-destructive_analysis_of_plant_physiological_traits_using_hyperspectral.pdf (5.53 MB)
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., “The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?”, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging”, Frontiers in Neuroscience, pp. 1-18, 2022.PDF icon Download paper (5.96 MB)
2021
P. Van Dyck, Froeling, M., Heusdens, C. H. W., Sijbers, J., Ribbens, A., and Billiet, T., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study”, Journal of Orthopaedic Research , vol. 39, pp. 1318–1330, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 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.
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)
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.
2020
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)
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.
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)
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)
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.
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.
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. Grammens, Van Haver, A., Danckaers, F., Booth, B. G., Sijbers, J., and Verdonk, P., “Small medial femoral condyle morphotype is associated with medial compartment degeneration and distinct morphological characteristics: a comparative pilot study”, Knee Surgery, Sports Traumatology, Arthroscopy, no. 686 , 2020.
K. Stanković, Huysmans, T., Danckaers, F., Sijbers, J., and Booth, B. G., “Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis”, Expert Systems With Applications, vol. 151, no. 113372, pp. 1-11, 2020.
P. Bladt, van Osch, M. J. P., Clement, P., Achten, E., Sijbers, J., and den Dekker, A. J., “Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling”, Magnetic Resonance in Medicine, vol. 84, no. 5, pp. 2523-2536, 2020.PDF icon Download paper (1.3 MB)
M. Bührer, Xu, H., Eller, J., Sijbers, J., Stampanoni, M., and Marone, F., “Unveiling Water Dynamics in Fuel Cells from Time-Resolved Tomographic Microscopy Data”, Scientific Reports, vol. 10, no. 16388 , 2020.PDF icon Download paper (4.12 MB)
2019
B. Bosmans, Huysmans, T., Lopes, P., Verhoelst, E., Dezutter, T., de Jaegere, P., Sijbers, J., Vander Sloten, J., and Bosmans, J., “Aortic root sizing for transcatheter aortic valve implantation using a shape model parameterisation”, Medical & Biological Engineering & Computing, vol. 57, no. 10, pp. 2081–2092, 2019.PDF icon Download paper (1.79 MB)
B. Bosmans, Huysmans, T., Lopes, P., Verhoelst, E., Dezutter, T., de Jaegere, P., Sijbers, J., Vander Sloten, J., and Bosmans, J., “Aortic root sizing for transcatheter aortic valve implantation using a shape model parameterisation”, Medical & Biological Engineering & Computing, vol. 57, no. 10, pp. 2081–2092, 2019.PDF icon Download paper (1.79 MB)

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