Publications

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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.
U. Roine, Ripatti, S., Rehnström, K., Roine, T., Kilpinen, H., Surakka, I., Wedenoja, J., Ylisaukko-oja, T., Kempas, E., Wessman, J., Moilanen, I., Mattila, M. - L., Kielinen, M., Jussila, K., Suomalainen, S., Pulkkinen, E., von Wendt, L., and Peltonen, L., “Reelin Associated With Restricted and Stereotyped Behavior Based on Principal Component Analysis on Autism Diagnostic Interview-Revised”, Autism - Open Access, vol. 3, no. 1, 2013.
T. Roine, Jeurissen, B., Leemans, A., Philips, W., and Sijbers, J., “Analysis and modeling of isotropic partial volume effects in diffusion MRI”, Frontiers in Neuroinformatics, vol. 7. 2013.
T. Roine, Pietilä, J., Kaartinen, J., Blanz, P., and Rantala, P., “Development of a Machine Vision System to Monitor a Grinding Mill Prototype”, in 12th European Symposium on Comminution and Classification (ESCC 2009), 2009.
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.
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)
J. Rozema, “On the wavefront aberrations of the human eye and the search for their origins”, University of Antwerp, Antwerp, 2004.
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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. 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.
K. Rafiezadeh Sahi, Rasti, B., Ghamisi, P., Scheunders, P., and Gloaguen, R., “When is the right time to apply denoising?”, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Gloaguen, R., and Scheunders, P., “MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6518-6530, 2022.PDF icon ms2a-net_multiscale_spectralspatial_association_network_for_hyperspectral_image_clustering.pdf (12.33 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P., and Gloaguen, R., “Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm”, Remote Sensing, vol. 12 (23), no. 4007, 2020.PDF icon remotesensing-12-04007-v2.pdf (21.88 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Jackisch, R., Rasti, B., Scheunders, P., and Gloaguen, R., “A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., “Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 15, pp. 284-296, 2022.PDF icon mdc_jstars-final_version.pdf (6.53 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., “Hyperspectral clustering using atrous spatial-spectral convolutional network”, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., “Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography”, Measurement Science and Technology, vol. 32, no. 035404, pp. 1-11, 2021.
J. Sanctorum, Adriaens, D., Dirckx, J. J. J., Sijbers, J., Van Ginneken, C., Aerts, P., and Van Wassenbergh, S., “Methods for characterization and optimisation of measuring performance of stereoscopic x-ray systems with image intensifiers”, Measurement Science and Technology, vol. 30, no. 10, 2019.
J. Sanctorum, Janssens, E., den Dekker, A. J., Senck, S., Heinzl, C., De Beenhouwer, J., and Sijbers, J., “A workflow to reconstruct grating-based X-ray phase contrast CT images: application to CFRP samples”, 4th Conference on X-ray and Neutron Phase Imaging with Gratings. Zürich, Switzerland, pp. 139-140, 2017.PDF icon Download poster (1008.67 KB)PDF icon Download abstract (294.87 KB)

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