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W. Van Hecke, Sijbers, J., De Backer, S., Poot, D. H. J., Parizel, P. M., and Leemans, A., “On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods”, NeuroImage, vol. 46, pp. 692-707, 2009.PDF icon Download paper (4.14 MB)
W. Van Hecke, Leemans, A., De Backer, S., Vandervliet, E., Parizel, P. M., Sijbers, J., and D'Agostino, E., “Non-rigid coregistration of diffusion tensor images using a viscous fluid model.”, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 191-192.
W. Van Hecke, Leemans, A., De Brabander, N., Laridon, A., Claeys, K., Ceulemans, B., Van Goethem, J., Parizel, P. M., and Sijbers, J., “Diffusion Tensor Fiber Tracking Reveals Probst Bundles in Patients with Agenesis of the Corpus Callosum”, in 32nd Congress of the Europea Society of NeuroRadiolog, 2007, p. 135.
W. Van Hecke, Leemans, A., De Backer, S., Vandervliet, E., Parizel, P. M., D'Agostino, E., and Sijbers, J., “Multi-channel coregistration of diffusion tensor images based on a viscous fluid model”, in Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium, Brussels, Belgium, 2006, pp. 139-142.
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., “A preliminary study of diffusion tensor imaging and tractography of the spinal cord in elderly”, in 21th Annual Symposium - Belgian Hospital Physicists Association, Ghent, Belgium, 2006, p. 61.
W. Van Hecke, Leemans, A., De Brabander, N., Laridon, A., Ceulemans, B., Sijbers, J., and Parizel, P. M., “Diffusion tensor fiber tracking in patients with agenesis of the corpus callosum”, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 34-35.
W. Van Hecke, Leemans, A., De Backer, S., Vandervliet, E., Sijbers, J., and Parizel, P. M., “A Ground Truth Analysis of the Preservation of Diffusion Tensor Information in a Population Specific Atlas”, International Society for Magnetic Resonance in Medicine - 16th Scientific Meeting. Toronto, Canada, 2008.
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., “Diffusion Tensor Tractoghraphy Reaveals Spinal Cord Alterations in Patients with Multiple Sclerosis”, in 32nd Congress of the Europea Society of NeuroRadiolog, 2007, p. 129.
W. Van Hecke, Leemans, A., Sijbers, J., Vandervliet, E., Van Goethem, J., and Parizel, P. M., “A tracking based DTI segmentation method for the detection of diffusion-related changes of the cervical spinal cord with aging”, Journal of Magnetic Resonance Imaging, vol. 27, pp. 978-991, 2008.PDF icon Download paper (4.4 MB)
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., “DTI of normal appearing spinal cord in elderly”, in 44th Annual Meeting of the American Society of Neuroradiology, San Diego, USA, 2006, pp. 380-381.
W. Van Hecke, Leemans, A., Vandervliet, E., Parizel, P. M., and Sijbers, J., “An optimized tensor orientation strategy for non-rigid alignment of DT-MRI data”, in Joint Annual Meeting ISMRM-ESMRMB, Berlin, 2007.
W. Van Hecke, Leemans, A., De Backer, S., Parizel, P. M., and Sijbers, J., “On the construction of a ground truth methodology to evaluate VBM analysis results of diffusion tensor images”, in European Society for Magnetic Resonance in Medicine and Biology, Valencia, Spain, 2008.
W. Van Hecke, Leemans, A., Sage, C. A., Veraart, J., Sijbers, J., and Sunaert, S., “The effect of template selection on diffusion tensor voxel based analysis results”, NeuroImage, vol. 55, pp. 566-573, 2011.
W. Van Hecke, “Improved Processing for Diffusion Tensor Magnetic Resonance Images for Coregistration, Atlas Construction, and Voxel Based Analysis”, University of Antwerp, Antwerp, 2009.PDF icon Download thesis (35.03 MB)
J. Van Houtte, “Surface and image-based registration methods with statistical modeling for biomedical applications”, 2023.PDF icon Download PhD thesis (29.72 MB)
J. Van Houtte, Sijbers, J., and Zheng, G., “Graphical User Interface for Joint Space Width Assessment by Optical Marker Tracking”, in 4th International Conference on Bio-engineering for Smart Technologies, 2021.
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.
J. Van Houtte, Audenaert, E., Zheng, G., and Sijbers, J., “Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images”, International Journal of Computer Assisted Radiology and Surgery, vol. 309, pp. 1333–1342, 2022.PDF icon Download paper (3.41 MB)
J. Van Houtte, Gao, X., Sijbers, J., and Zheng, G., “2D/3D registration with a statistical deformation model prior using deep learning”, in the IEEE International Conference on Biomedical and Health Informatics (BHI'21) , 2021, pp. 1-4.PDF icon Download paper (1.41 MB)
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.
J. Van Houtte, Vandenberghe, F., Zheng, G., Huysmans, T., and Sijbers, J., “EquiSim: An open-source articulatable statistical model of the equine distal limb”, Frontiers in Veterinary Science , vol. 8, no. 75, 2021.
V. Van Meir, Huysmans, T., Sijbers, J., and Van Der Linden, A., “Statistical shape and position analysis on 3D structural MRI data of a motor region involved in vocal behavior of songbirds”, in Proceedings of the International Society for Magnetic Resonance in Medicine, Berlin, Germany, 2007, p. 431.PDF icon Full text (122.28 KB)
V. Van Meir, Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., Sijbers, J., Verhoye, M., Balthazart, J., and Van Der Linden, A., “Spatiotemporal properties of the BOLD response in the songbirds auditory circuit during a variety of listening tasks”, NeuroImage, vol. 25, pp. 1242-1255, 2005.
V. Van Meir, Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., Sijbers, J., Verhoye, M., Balthazart, J., and Van Der Linden, A., “Functional Magnetic resonance Imaging meets animal vocal learner”, in Third One-Day Symposium of Young Belgian Magnetic Resonance Scientists, Brussels, Belgium, 2004.
V. Van Nieuwenhove, “Model-based reconstruction algorithms for dynamic X-ray CT”, 2017.PDF icon Download thesis (4.65 MB)

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