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T. Roine, Jeurissen, B., Philips, W., Leemans, A., and Sijbers, J., “Isotropic non-white matter partial volume effects in constrained spherical deconvolution”, Sixth Annual Meeting of the Benelux ISMRM Chapter. 2014.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Leemans, A., and Sijbers, J., “Informed constrained spherical deconvolution (iCSD)”, Medical Image Analysis, vol. 24, no. 1, pp. 269–281, 2015.PDF icon Download accepted manuscript (987.95 KB)
T. Roine, Jeurissen, B., Philips, W., Leemans, A., and Sijbers, J., “Improving fiber orientation estimation in constrained spherical deconvolution under non-white matter partial volume effects”, Proceedings of the Joint Annual Meeting ISMRM–ESMRMB. p. 4492, 2014.PDF icon 4492.pdf (574.06 KB)
U. Roine, Roine, T., Salmi, J., Nieminen-von Wendt, T., Leppämäki, S., Rintahaka, P., Tani, P., and Sams, M., “DTI-based Classification of Affection Status in Asperger Syndrome.”, Society for Neuroscience Annual Meeting (Neuroscience 2012). 2012.
U. Roine, Salmi, J., Roine, T., Nieminen-von Wendt, T., Leppämäki, S., Rintahaka, P., Tani, P., Leemans, A., and Sams, M., “Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome”, Molecular Autism, vol. 6, p. 4, 2015.PDF icon Download paper (1.75 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., “Isotropic non-white matter partial volume effects in constrained spherical deconvolution”, Frontiers in Neuroinformatics, vol. 8, pp. 1-9, 2014.PDF icon Download paper (1.79 MB)
T. Roine, “Improved reliability of fiber orientation estimation and graph theoretical analysis of structural brain networks with diffusion MRI”, University of Antwerp, 2017.
U. Roine, Roine, T., Salmi, J., Nieminen-von Wendt, T., Tani, P., Leppämäki, S., Rintahaka, P., Caeyenberghs, K., Leemans, A., and Sams, M., “Abnormal wiring of the connectome in adults with high-functioning autism spectrum disorder”, Molecular Autism, vol. 6, p. 65, 2015.PDF icon Download paper (1.64 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., “Isotropic non-white matter partial volume effects in constrained spherical deconvolution”, Information-based methods for neuroimaging: analyzing structure, function and dynamics, p. 112, 2015.
T. Roine, Kaartinen, J., and Lamberg, P., “Training Simulator for Flotation Process Operators”, in 18th IFAC World Congress, 2011.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Sijbers, J., and Leemans, A., “Methodological Considerations on Graph Theoretical Analysis of Structural Brain Networks”, Proc. Intl. Soc. Mag. Reson. Med. 24. p. 3437, 2016.
M. Roshani, Phan, G., Roshani, G. Hossein, Hanus, R., Corniani, E., and Nazemi, E., “Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows”, Measurement, vol. 168, 2021.
M. Roshani, Phan, G., Faraj, R. Hassan, Phan, N. - H., Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products”, Nuclear Engineering and Technology, 2020.PDF icon 1-s2.0-s1738573320308779-main.pdf (1.38 MB)
M. Roshani, Phan, G. T. T., Roshani, G. Hossein, Hanus, R., Duong, T., Corniani, E., Nazemi, E., and Kalmouni, E. M., “Evaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline’s scale layer thickness”, Alexandria Engineering Journal, vol. 60, 2021.
M. Roshani, Sattari, M. Amir, Ali, P. Jammal Muh, Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter”, Flow Measurement and Instrumentation, vol. 75, 2020.
J. Rozema, “On the wavefront aberrations of the human eye and the search for their origins”, University of Antwerp, Antwerp, 2004.
J. Ruano-Balseca, Bravo, D., Giraldo, D., Gómez, M., Gonzalez, F. A., and Romero, E., “Spatio-temporal characterization of gastric distensibility in upper endoscopy identifies the presence of Helicobacter pylori”, IEEE Transactions on Medical Imaging, pp. 1-1, 2026.
J. Ruano-Balseca, Bravo, D., Giraldo, D., Gómez, M., Gonzalez, F. A., Manzanera, A., and Romero, E., “Estimating Polyp Size From a Single Colonoscopy Image Using a Shape-From-Shading Model”, in 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024, pp. 1-5.
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E. Ribeiro Sabidussi, Klein, S., 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”, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
E. Ribeiro Sabidussi, Nicastro, M., Bazrafkan, S., Beirinckx, Q., Jeurissen, B., Sijbers, J., den Dekker, A. J., Klein, S., and Poot, D. H. J., “A deep learning approach to T1 mapping in quantitative MRI”, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology (ESMRMB), Rotterdam, The Netherlands, vol. 32 (Suppl. 1). Magn Reson Mater Phy, 2019.
E. R. Sabidussi, Klein, S., Jeurissen, B., and Poot, D. H. J., “dtiRIM: A recurrent inference machine for diffusion tensor estimation”, Proc Intl Soc Mag Reson Med 30. p. 1981, 2022.
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.
E. Ribeiro Sabidussi, Klein, S., Jeurissen, B., and Poot, D. H. J., “dtiRIM: A generalisable deep learning method for diffusion tensor imaging”, Neuroimage, vol. 269, 2023.PDF icon Download paper (5.11 MB)
C. C. Sabino, Andrade, L. S., Tsang, I. R., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., “Motion Compensation Techniques in Permutation-Based Video Encryption”, in Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics, Washington, DC, USA, 2013, pp. 1578–1581.
C. A. Sage, Van Hecke, W., Peeters, R. R., Sijbers, J., Robberecht, W., Parizel, P. M., Marchal, G., Leemans, A., and Sunaert, S., “Quantitative diffusion tensor imaging in amyotrophic lateral sclerosis: revisited.”, Human brain mapping, vol. 30, no. 11, pp. 3657-75, 2009.

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