Publications

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Author Type [ Year(Asc)]
In Press
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, In Press.
2020
D. Frenkel, De Beenhouwer, J., and Sijbers, J., “An adaptive probability map for the Discrete Algebraic Reconstruction Technique”, 10th Conference on Industrial Computed Tomography (ICT 2020). 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 Fibers”, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.PDF icon Download paper (703.79 KB)
A. Presenti, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., “Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT”, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
2019
S. Mukunthan, Vleugels, J., Huysmans, T., Mayor, T. Sotto, and De Bruyne, G., “A 3D Printed Thermal Manikin Head for Evaluating Helmets for Convective and Radiative Heat Loss”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) Volume VII, 2019, vol. VII, pp. 592–602.
F. Danckaers, Huysmans, T., and Sijbers, J., “Adaptable digital human models from 3D body scans”, in DHM and Posturography, vol. VI, Academic Press, 2019, pp. 459-470.
B. G. Booth, Keijsers, N. L. W., Huysmans, T., and Sijbers, J., “Advancing Analysis Techniques for Plantar Pressure Videos via Open-Access Contributions”, IEEE International Symposium on Biomedical Imaging (ISBI'19) . 2019.PDF icon Download abstract (86 KB)
E. Pechenkova, Nosikova, I., Rumshiskaya, A., Litvinova, L., Rukavishnikov, I., Mershina, E., Sinitsyn, V., Van Ombergen, A., Jeurissen, B., Jillings, S., Laureys, S., Sijbers, J., Grishin, A., Chernikova, L., Naumov, I., Kornilova, L., Wuyts, F. L., Tomilovskaya, E., and Kozlovskaya, I., “Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI.”, Front Physiol, vol. 10, p. 761, 2019.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., “Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform”, Computers and Electronics in Agriculture, vol. 162, pp. 749-758, 2019.
J. Van Houtte, Stanković, K., Booth, B. G., Danckaers, F., Bertrand, V., Verstreken, F., Sijbers, J., and Huysmans, T., “An Articulating Statistical Shape Model of the Human Hand”, in Advances in Human Factors in Simulation and Modeling (AHFE 2018), Cham, 2019, vol. 780, pp. 433–445.
P. Van Dyck, Zazulia, K., Smekens, C., Heusdens, C. H. W., Janssens, T., and Sijbers, J., “Assessment of Anterior Cruciate Ligament Graft Maturity With Conventional Magnetic Resonance Imaging”, The Orthopaedic Journal of Sports Medicine, vol. 7, no. 6, pp. 1-9, 2019.PDF icon Download paper (202.39 KB)
B. G. Booth, Keijsers, N. L. W., Sijbers, J., and Huysmans, T., “An assessment of the information lost when applying data reduction techniques to dynamic plantar pressure measurements”, Journal of Biomechanics , vol. 87, pp. 161-166, 2019.
J. Fatermans, den Dekker, A. J., O'Leary, C. M., Nellist, P. D., and Van Aert, S., “Atom column detection from STEM images using the maximum a posteriori probability rule”, MC 2019, Berlin, Germany. 2019.
J. Fatermans, den Dekker, A. J., and Van Aert, S., “Atom detection from electron microscopy images”, RBSM 2019, Louvain-la-Neuve, Belgium. p. 15, 2019.
F. Danckaers, Scataglini, S., Haelterman, R., Van Tiggelen, D., Huysmans, T., and Sijbers, J., “Automatic Generation of Statistical Shape Models in Motion”, in Advances in Human Factors in Simulation and Modeling (AHFE 2018), Cham, 2019, vol. 780, pp. 170–178.
P. Bladt, van Osch, M. J. P., Achten, E., den Dekker, A. J., and Sijbers, J., “Beyond the consensus: is sacrificing part of the PCASL scan time for measurement of labeling efficiency and T1 of blood beneficial?”, University of Michigan international workshop on arterial spin labeling MRI: technical updates and clinical experience, March 9-10 2019, Ann Arbor, USA. 2019.PDF icon Download abstract (1.31 MB)
P. Bladt, van Osch, M. J. P., Achten, E., den Dekker, A. J., and Sijbers, J., “Beyond the consensus: should measurement of T1 of blood and labeling efficiency be included and should a single- or multi-PLD protocol be used in a five-minute protocol for PCASL?”, 11th Annual Meeting of ISMRM Benelux, January 17th 2019, Leiden, The Netherlands. 2019.
P. Bladt, van Osch, M. J. P., Achten, E., den Dekker, A. J., and Sijbers, J., “Beyond the consensus: what to include when 5 minutes are available for perfusion imaging by PCASL?”, 27th Annual Meeting of ISMRM, Montreal, Canada. 2019.
A. Van Ombergen, Jillings, S., Jeurissen, B., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E. V., Rukavishnikov, I., Manko, O., Danylichev, S., R. Rühl, M., Kozlovskaya, I. B., Sunaert, S., Parizel, P. M., Sinitsyn, V., Laureys, S. S. L., Sijbers, J., Eulenburg, Pzu, and Wuyts, F. L., “Brain ventricular volume changes induced by long-duration spaceflight”, Proceedings of the National Academy of Sciences, vol. 116, no. 21, pp. 10531-10536, 2019.
H. Verhelst, Giraldo, D., Linden, C. Vander, Vingerhoets, G., Jeurissen, B., and Caeyenberghs, K., “Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis.”, Neurorehabil Neural Repair, p. 1545968319868720, 2019.
M. Van Dael, Verboven, P., Zanella, A., Sijbers, J., and Nicolai, B., “Combination of shape and X-ray inspection for apple internal quality control: in silico analysis of the methodology based on X-ray computed tomography”, Postharvest Biology and Technology, vol. 148, pp. 218-227, 2019.
L. Goto, Huysmans, T., Lee, W., Molenbroek, J. F. M., and Goossens, R., “A Comparison Between Representative 3D Faces Based on Bi- and Multi-variate and Shape Based Analysis”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)- Volume VII, 2019, vol. VII, pp. 1355–1364.
V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., “Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields”, Remote Sensing, vol. 11, 2019.
J. Van Houtte, Bazrafkan, S., Vandenberghe, F., Zheng, G., and Sijbers, J., “A Deep Learning Approach to Horse Bone Segmentation from Digitally Reconstructed Radiographs”, in International Conference on Image Processing Theory, Tools, and Applications, 2019.
E. Ribeiro Sabidussi, Nicastro, M., Bazrafkan, S., Beirinckx, Q., Jeurissen, B., den Dekker, A. J., Klein, S., and Poot, D. H. J., “A deep learning approach to T1 mapping in quantitative MRI”, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands, vol. 32 (Suppl. 1). Magn Reson Mater Phy, 2019.

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