Publications

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V
Aja-Fernández, S., C. Martín-Martín, Á. Planchuelo-Gómez, A. Faiyaz, M. Nasir Uddin, G. Schifitto, A. Tiwari, S. J. Shigwan, R. Kumar Singh, T. Zheng, et al., "Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies", NeuroImage: Clinical, vol. 39, pp. 103483, 2023.
C
de Luis-García, R., C. Alberola-Lopez, and C-F. Westin, "On the choice of a tensor distance for DTI white matter segmentation", New Developments in the Visualization and Processing of Tensor Fields: Springer Berlin Heidelberg, pp. 283–306, 2012.
G
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", bioRxiv, 2021.
De Luca, A., A. Ianus, A. Leemans, M. Palombo, N. Shemesh, H. Zhang, D. C. Alexander, M. Nilsson, M. Froeling, G-J. Biessels, et al., "On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge", NeuroImage, pp. 118367, 2021.
N
Tristán-Vega, A., C-F. Westin, and S. Aja-Fernández, "A new methodology for the estimation of fiber populations in the white matter of the brain with the Funk–Radon transform", NeuroImage, vol. 49, no. 2: Academic Press, pp. 1301–1315, 2010.
Martin-Fernandez, M., R. San Jose-Estepar, C-F. Westin, and C. Alberola-Lopez, "A novel Gauss-Markov random field approach for regularization of diffusion tensor maps", Computer Aided Systems Theory-EUROCAST 2003: Springer Berlin Heidelberg, pp. 506–517, 2003.
Zhang, H., C. Luo, Q. Wang, M. Kitchin, A. Parmley, J. Monge-Alvarez, and P. Casaseca-de-la-Higuera, "A novel infrared video surveillance system using deep learning based techniques", Multimedia Tools and Applications, vol. 77, issue 26676, 2018.

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