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J. Sijbers, Van Der Linden, A., Scheunders, P., Van Audekerke, J., Raman, E., and Van Dyck, D., “Semi-automatic mouse cerebellum extraction from 3D magnetic resonance data”, in Proceedings of the International Society for Magnetic Resonance in Medicine, New York, USA, 1996, vol. 3, p. 1585.
J. Sijbers and De Beenhouwer, J., “Mobile imaging of an object using penetrating radiation”, U.S. Patent WO/2017/1783342017.
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.
J. Sijbers, “Estimation of Signal and Noise from Magnitude Magnetic Resonance Images”, 1998.PDF icon Download PhD thesis (3.5 MB)
J. Sijbers, Michiels, I., Verhoye, M., Van Audekerke, J., Van Der Linden, A., and Van Dyck, D., “Restoration of MR induced artifacts in simultaneously recorded MR/EEG data”, Magnetic Resonance Imaging, vol. 17, pp. 1383-1393, 1999.PDF icon Download paper (1.09 MB)
J. Sijbers, Van Audekerke, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Reduction of ECG and gradient related artifacts in simultaneously recorded human EEG/MRI data”, Magnetic Resonance Imaging, vol. 18, pp. 881-886, 2000.PDF icon Download paper (2 MB)
J. Sijbers and Postnov, A., “Reduction of ring artifacts in high resolution micro-CT images”, in Advanced Concepts for Intelligent Vision Systems (ACIVS), Brussels, Belgium, 2004.
J. Sijbers, Verhoye, M., Scheunders, P., Van Der Linden, A., Van Audekerke, J., Van Dyck, D., and Raman, E., “Segmentation Scheme for Volume Quantization from 3D Microscopic MR images”, in Proceedings of the Joint Meeting NVvM & BVM, Gent, 1996, pp. 168-169.
J. Sijbers and den Dekker, A. J., “Longitudinal Magnetic Resonance Imaging Method”, U.S. Patent WO2024100240A12024.
J. Sijbers, De Beenhouwer, J., Ling, Y. - T., and Vandervorst, W., “A reconstruction method for atom probe tomography”, U.S. Patent 180175752023.
J. Sijbers, Ceulemans, T., and Van Dyck, D., “Algorithm for the computation of 3D Fourier descriptors”, in 16th International Conference on Pattern Recognition, Quebec, Canada, 2002, pp. 790-793.PDF icon Download paper (665.86 KB)
J. Sijbers, den Dekker, A. J., and Bos, R., “A likelihood ratio test for functional MRI data analysis to account for colored noise”, Lecture Notes in Computer Science, vol. 3708, pp. 538-546, 2005.PDF icon Download full paper (483.15 KB)
J. Sijbers, Michiels, I., Verhoye, M., Van Audekerke, J., Van Der Linden, A., and Van Dyck, D., “Automatic, adaptive filter for MRI related artefacts in simultaneously recorded EEG/MRI data”, in Third Meeting Belgian Society for Neuroscience, 1999.
J. Sijbers, den Dekker, A. J., Raman, E., and Van Dyck, D., “Parameter estimation from magnitude MR images”, International Journal of Imaging Systems and Technology, vol. 10, pp. 109-114, 1999.PDF icon Download paper (350.44 KB)
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, vol. 40, no. 13-14, pp. 1317-1338, 2023.
M. Siqueira Pinto, Anania, V., Paolella, R., Smekens, C., Billiet, T., Janssens, T., den Dekker, A. J., Sijbers, J., Guns, P. - J., and Van Dyck, P., “Harmonization of diffusion MRI on healthy subjects using NeuroCombat and LongCombat: a B-Q MINDED Brain Intra-and Inter-Scanner Study”, Frontiers in Neuroscience, vol. 19, 2025.
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., “Harmonisation of Brain Diffusion MRI: Concepts and Methods”, Frontiers in Neuroscience , vol. 14, pp. 1-17, 2020.PDF icon Download paper (2.61 MB)
M. Siqueira Pinto, Winzeck, S., Correia, M. M., Kornaropoulos, E. N., Menon, D. K., Glocker, B., den Dekker, A. J., Sijbers, J., Guns, P. - J., Van Dyck, P., and Newcombe, V. F. J., “Outcome prediction in Mild Traumatic Brain Injury patients using conventional and diffusion MRI via Support Vector Machine: A CENTER-TBI study”, ISMRM & SMRT Annual Meeting. 2021.
M. Siqueira Pinto, Winzeck, S., Richter, S., Correia, M. M., Kornaropoulos, E. N., Menon, D. K., Glocker, B., Guns, P. - J., den Dekker, A. J., Sijbers, J., Newcombe, V. F. J., and Van Dyck, P., “Outcome prediction of mild traumatic brain injury using support vector machine based on longitudinal MRdiffusion imaging from CENTER-TBI”, Magn Reson Mater Phy (ESMRMB), vol. 34. p. S54, 2021.
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., “Voxelwise harmonisation of FA on a cohort of 605 healthy subjects using ComBat: an exploratory study”, ESMRMB 2019, 36th Annual Scientific Meeting, Rotterdam, NL. 2019.
N. Six, Renders, J., Sijbers, J., and De Beenhouwer, J., “Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images”, IEEE Transactions on Computational Imaging, vol. 7, pp. 1304-1313, 2021.
N. Six, De Beenhouwer, J., Van Nieuwenhove, V., Vanroose, W., and Sijbers, J., “Joint reconstruction and flat-field estimation using support estimation”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.PDF icon Download paper (1.53 MB)
N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps”, Optics Express, vol. 32, no. 2, pp. 1135-1150, 2024.PDF icon Download paper (13.42 MB)
N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., “Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps”, in SPIE Optical Engineering: Developments in X-Ray Tomography XIV , 2022, vol. 12242, p. 122420O.
N. Six, De Beenhouwer, J., and Sijbers, J., “poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT”, Optics Express, vol. 27, no. 23, pp. 33427-33435, 2019.PDF icon Download paper (997.08 KB)

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