Publications

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Conference Paper
Á. Marinovszki, De Beenhouwer, J., and Sijbers, J., An efficient CAD projector for X-ray projection based 3D inspection with the ASTRA Toolbox, in 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018.PDF icon Download paper (364.16 KB)
R. Pinho, Sijbers, J., and Vos, W., Efficient approaches to intrathoracic airway tree segmentations, in Proceedings of the Biomedical Engineering IEEE/EMBS Benelux Symposium, Brussels, Belgium, 2006, vol. 2, pp. 151-154.PDF icon Download paper (515.86 KB)
J. Sijbers and Van Dyck, D., Efficient algorithm for the computation of 3D Fourier descriptors, in 1st International Symposium on 3D Data Processing Visualization and Transmission, Padua, Italy, 2002, pp. 640-643.
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., Effect of beam hardening on resolution in x-ray microtomography, in SPIE Medical Imaging: Image Processing, San Diego CA, USA, 2004, vol. 5370, pp. 2089-2096.PDF icon Download paper (156.85 KB)
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., The effect of beam hardening on MTF measurements in X-ray microtomography, in 19th Annual Symposium of the Belgian Hospital Physicists Association, 2004.
G. Van Eyndhoven, De Beenhouwer, J., and Sijbers, J., A dynamic region estimation method for cerebral perfusion CT, in 6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS), 2016, pp. 331-342.PDF icon Download paper (840.01 KB)
V. Van Nieuwenhove, De Beenhouwer, J., and Sijbers, J., Dynamic flat field correction in X-ray computed tomography, in Optimess conference, 2016, Antwerp.
A. Dabravolski, Batenburg, K. J., and Sijbers, J., Dynamic Angle Selection in X-ray Computed Tomography, in 1st International Conference on Tomography of Materials and Structures (ICTMS), Ghent, Belgium, 2013, pp. 27-30.PDF icon Download full paper (447.03 KB)PDF icon Download presentation (682.25 KB)
A. Presenti, Sijbers, J., and De Beenhouwer, J., Dynamic angle selection for few-view X-ray inspection of CAD based objects, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.
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.
D. Van Dyck, den Dekker, A. J., Sijbers, J., and Bettens, E., Dose Limited Resolution, in Proceedings Microscopy and Microanalysis, Atlanta, Georgia, U.S.A, 1998, vol. 2, pp. 802-803.
K. J. Batenburg and Sijbers, J., Discrete tomography from micro-CT data: application to the mouse trabecular bone structure, in Proceedings of SPIE Medical Imaging: Physics of Medical Imaging, San Diego, CA, USA, 2006, vol. 6142, pp. 1325-1335.PDF icon Download full paper (563.79 KB)
G. Van Gompel, Batenburg, K. J., Van de Casteele, E., Van Aarle, W., and Sijbers, J., A discrete tomography approach for superresolution micro-CT images, in IEEE International Symposium on Biomedical Imaging, Rotterdam, 2010, pp. 816-819.PDF icon Download paper (1.13 MB)
W. Van Aarle, Cant, J., De Beenhouwer, J., and Sijbers, J., Discrete tomographic reconstruction from deliberately motion blurred X-ray projections, in 6th Conference on Industrial Computed Tomography, Wels, Austria, 2016, pp. 1-6.PDF icon Download paper (444.66 KB)
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, 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.
Z. Mai, Verhoye, M., Van Der Linden, A., and Sijbers, J., Diffusion Tensor Images Upsampling: a Registration-based Approach, in 13th International Machine Vision and Image Processing Conference, Dublin, Ireland, 2009, vol. 13, pp. 36-40.PDF icon Download paper (808.21 KB)
Z. Mai, Verhoye, M., and Sijbers, J., Diffusion Tensor Images Edge-Directed Interpolation, in International Symposium on Biomedical Imaging 2010, 2010, pp. 732-735.
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 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.
A. J. den Dekker and Sijbers, J., Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test, in Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, 2004, pp. 233-236.
S. Delputte, Leemans, A., Fieremans, E., De Deene, Y., D'Asseler, Y., Lemahieu, I., Achten, E., Sijbers, J., and Van de Walle, R., Density Regularized Fiber Tractography of the Brain White Matter using Diffusion Tensor MRI, in 13th Scientific Meeting - International Society for Magnetic Resonance in Medicine, Miami, USA, 2005, p. 1309.
J. Rajan, Jeurissen, B., Sijbers, J., and Kannan, K., Denoising Magnetic Resonance Images using Fourth Order Complex Diffusion, in 13th International Machine Vision and Image Processing Conference, Dublin, Ireland, 2009, pp. 123-127.
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.
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.

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