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V. Van Nieuwenhove, De Beenhouwer, J., and Sijbers, J., “Dynamic flat field correction in X-ray computed tomography”, in Optimess conference, 2016, Antwerp.
V. Van Nieuwenhove, De Beenhouwer, J., Vlassenbroeck, J., Brennan, M., and Sijbers, J., “MoVIT: A tomographic reconstruction framework for 4D-CT”, Optics Express, vol. 25, no. 16, pp. 19236-19250, 2017.
V. Van Nieuwenhove, Van Eyndhoven, G., De Beenhouwer, J., and Sijbers, J., “Compensation of affine deformations in fan and cone beam projections”, Micro-CT User Meeting. pp. 187-189, 2014.PDF icon Download abstract (285.55 KB)
V. Van Nieuwenhove, Van Eyndhoven, G., Batenburg, K. J., Buls, N., Vandemeulebroucke, J., De Beenhouwer, J., and Sijbers, J., “Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT”, Medical Physics, vol. 43, no. 12, pp. 6429-6438, 2016.
V. Van Nieuwenhove, De Beenhouwer, J., and Sijbers, J., “A fast 4D CT reconstruction algorithm for affine deforming objects”, Applied inverse problems conference. 2015.
V. Van Nieuwenhove, De Beenhouwer, J., De Schryver, T., Van Hoorebeke, L., and Sijbers, J., “Data-Driven Affine Deformation Estimation and Correction in Cone Beam Computed Tomography”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1441-1451, 2017.
V. Van Nieuwenhove, De Beenhouwer, J., De Schryver, T., Van Hoorebeke, L., and Sijbers, J., “Affine deformation correction in cone beam Computed Tomography”, in Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Newport, Rhode Island, USA, 2015, pp. 182-185.
V. Van Nieuwenhove, De Beenhouwer, J., Vlassenbroeck, J., Moesen, M., Brennan, M., and Sijbers, J., “Registration Based SIRT: A reconstruction algorithm for 4D CT”, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (2.36 MB)
V. Van Nieuwenhove, De Beenhouwer, J., De Carlo, F., Mancini, L., Marone, F., and Sijbers, J., “Dynamic intensity normalization using eigen flat fields in X-ray imaging”, Optics Express, vol. 23, no. 21, pp. 27975-27989, 2015.Package icon Download Matlab code (2.92 MB)PDF icon Download paper (1.68 MB)
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.
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, 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, 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, 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.
J. Van Houtte, “Surface and image-based registration methods with statistical modeling for biomedical applications”, 2023.PDF icon Download PhD thesis (29.72 MB)
W. Van Hecke, Nagels, G., Leemans, A., Vandervliet, E., Sijbers, J., and Parizel, P. M., “Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis”, Journal of magnetic resonance imaging, vol. 31, pp. 1492-1498, 2010.
W. Van Hecke, Leemans, A., D'Agostino, E., De Backer, S., Vandervliet, E., Parizel, P. M., and Sijbers, J., “The evaluation of a population based diffusion tensor image atlas using a ground truth method”, in Proceedings of SPIE Medical Imaging, San Diego, USA, 2008, vol. 6914.
W. Van Hecke, Leemans, A., D'Agostino, E., De Backer, S., Vandervliet, E., Parizel, P. M., and Sijbers, J., “Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information”, IEEE Transactions on Medical Imaging, vol. 26, pp. 1598-1612, 2007.PDF icon Download paper (1.85 MB)
W. Van Hecke, Leemans, A., Sijbers, J., Parizel, P. M., and Van Goethem, J., “A comparison of diffusion tensor analysis methods for detecting age-related changes of the normal appearing spinal cord”, in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 293-294.
W. Van Hecke, Sijbers, J., Van Goethem, J., and Parizel, P. M., “Diffusion tensor tractography reveals white matter alterations in the normal appearing spinal cord of Multiple Sclerosis patients”, in European Society for Magnetic Resonance in Medicine and Biology, Valencia, Spain, 2008.
W. Van Hecke, Nagels, G., Emonds, G., Leemans, A., Sijbers, J., van Goethem, J., and Parizel, P. M., “A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions.”, Journal of magnetic resonance imaging : JMRI, vol. 30, no. 1, pp. 25-34, 2009.PDF icon Download paper (902.67 KB)

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