Publications

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Conference Abstract
S. Van Aert, De Backer, A., De wael, A., Fatermans, J., E Irmak, A., Friedrich, T., Lobato, I., Jones, L., den Dekker, A. J., Nellist, P. D., and Bals, S., “Strategies for quantifying the 3D atomic structure and the dynamics of nanomaterials using model-based STEM”, Virtual MRS Spring/ Fall Meeting, Boston, United States (online). 2020.
Z. Wang, Rogge, S., Van Dael, M., Van Nieuwenhove, V., Verboven, P., Sijbers, J., and Nicolai, B., “Understanding microstructural deformation of apple tissue from 4D micro-CT imaging”, ISHS Symposium 2016: Sensing Plant Water Status - Methods and Applications in Horticultural Science. Potsdam, Germany, 5-7 October. 2016.
N. J. Forde, Ellison-Wright, I., Nathan, P. J., Zaman, R., Dudas, R., Agius, M., Fernandez-Egea, E., Leemans, A., Jeurissen, B., Scanlon, C., McDonald, C., and Cannon, D. M., “White Matter Tract Deficits in Schizophrenia”, Neuroscience Ireland Conference, vol. 7. Dublin, Ireland, 2011.
Conference Paper
W. Van Aarle, Van Gompel, G., Batenburg, K. J., Van de Casteele, E., and Sijbers, J., “A 3-dimensional discrete tomography approach for superresolution micro-CT images: application to foams”, in The first international conference on image formation in X-ray computed tomography, 2010, pp. 45-48.PDF icon Download full paper (816.87 KB)
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F, San Diego, CA, United States, 2022.
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography”, in e-Journal of Nondestructive Testing, 2022, vol. 27 (3), pp. 1-5.
T. Nath, G.Liu,, Weyn, B., Hassan, B., De Backer, S., and Scheunders, P., “Automated Social behaviour Recognition At Low Resolution”, in 22nd IEEE - International Conference of Pattern Recognition (ICPR), 2014.
V. Nguyen, De Beenhouwer, J., Bazrafkan, S., Hoang, A. - T., Van Wassenbergh, S., and Sijbers, J., “BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 518-521.PDF icon Download paper (2.16 MB)
D. Iuso, Nazemi, E., Six, N., De Samber, B., De Beenhouwer, J., and Sijbers, J., “CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts”, in IEEE ICIP, 2021.
E. Vandervliet, Nagels, G., Heinecke, A., Van Hecke, W., Leemans, A., Sijbers, J., and Parizel, P. M., “On the cause and mechanisms of the negative BOLD response in fMRI”, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, p. 308.
M. Van Dael, Verboven, P., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., “Comparison of methods for online inspection of apple internal quality”, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (815.39 KB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
L. F. Alves Pereira, Janssens, E., Van Dael, M., Verboven, P., Nicolai, B., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., “Fast X-ray Computed Tomography via Image Completion”, in 6th Conference on Industrial Computed Tomography(iCT), Wels, Austria, 2016, pp. 1-5.
G. Nagels, Vandervliet, E., Van Hecke, W., Engelborghs, S., hooghe, M. B. D., Cras, P., Parizel, P. M., and De Deyn, P. P., “fMRI during PASAT and PVSAT in mild MS, moderate MS and normal volunteers.”, in 22nd Congress of the European Committee for, Madrid, Spain, 2006.
J. Van Audekerke, Verhoye, M., Sijbers, J., DeVoogd, T. J., Smulders, T., Newman, S. W., and Van Der Linden, A., “Imaging birds .. in a bird cage: In vivo MRI microscopy of the canary brain at 7T”, in Proceedings of International Society for Magnetic Resonance in Medicine: Sixth Annual Meeting, 1998, vol. 2, pp. 162-163.
N. Van Camp, Verhoye, M., Leemans, A., Postnov, A., Beque, D., Van den Eynden, J., Nuyts, J., Lauwers, E., Verbruggen, A., Debyser, Z., Baekelandt, V., De Clerck, N., Sijbers, J., Van Laere, K., and Van Der Linden, A., “In vivo multimodal imaging of a rat model for Parkinson’s disease: high resolution micro-MRI, micro-SPECT and micro-CT”, in 21th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology, Copenhagen, Denmark, 2004, pp. 22-23.
N. Van Camp, Van Laere, K., Vreys, R., Verhoye, M., Lauwers, E., Beque, D., Maes, F., Verbruggen, A., Debyser, Z., Mortelmans, L., Sijbers, J., Nuyts, J., Baekelandt, V., and Van Der Linden, A., “In vivo multimodal (MRI, SPECT) imaging of the 6-OHDA rat model for Parkinson’s disease correlated with behavior and histology”, in Belgian Society of Neuroscience, 2005.
N. Van Camp, Van Laere, K., Vreys, R., Verhoye, M., Lauwers, E., Beque, D., Maes, F., Verbruggen, A., Debyser, Z., Mortelmans, L., Sijbers, J., Nuyts, J., Baekelandt, V., and Van Der Linden, A., “In vivo multimodal (MRI,SPECT) imaging of the 6-OHDA rat model for Parkinson’s disease correlated with behavior and histology”, in XXIInd International Symposium on Cerebral Blood Flow, Metabolism and Function and VIIth International Conference of Quantification of Brain Function with PET, Vrije Universiteit, Amsterdam, the Netherlands, 2005.
S. Sterckx, Coppin, P., De Backer, S., Debruyn, W., Kempeneers, P., Meuleman, K., Nackaerts, K., Reusen, I., and Scheunders, P., “Information extraction techniques for monitoring of stress symptoms in orchards”, in Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen, 2003, pp. 278-283.
K. Van Slambrouck, Van Gompel, G., Defrise, M., Batenburg, K. J., Sijbers, J., and Nuyts, J., “Iterative correction of beam hardening artifacts in CT”, in The First International Conference on Image Formation in X-Ray Computed Tomography, 2010.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., “A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
E. Janssens, De Beenhouwer, J., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., “Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt”, in IEEE International Conference on Image Processing, 2015, pp. 917-921.
K. Meuleman, Coppin, P., De Backer, S., Debruyn, W., Nackaerts, K., Scheunders, P., and Sterckx, S., “Optimal hyperspectral indicators for stress detection in orchards”, in Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen, 2003, pp. 534-541.
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)
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.

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