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S
Sanchez-Ferrero, G. V., and J. I. Arribas, "A statistical-genetic algorithm to select the most significant features in mammograms", Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4673 LNCS, pp. 189-196, 2007.
N
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.
San-Jose-Revuelta, L. Miguel, M. Martin-Fernandez, and C. Alberola-Lopez, "A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images", Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on: IEEE, pp. 1–4, 2007.
San-Jose-Revuelta, L. Miguel, M. Martin-Fernandez, and C. Alberola-Lopez, "A new method for fiber tractography in diffusion tensor magnetic resonance images", Proc. of the IEEE Int’l Conf. on Signal and Image Processing, ICSIP, vol. 6, pp. 380–385, 2006.
Sabzi, S., Y. Abbaspour-Gilandeh, and J. I. Arribas, "A new method based on computer vision for non-intrusive orange peel sorting", 2017 56th FITCE Congress: IEEE, 2017.
San-José-Revuelta, L. M., and P. Casaseca-de-la-Higuera, "A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems", Soft Computing: Springer Berlin Heidelberg, pp. 1–15, 2000, 2020.
San-Jose-Revuelta, L. M., and J. I. Arribas, "A new approach for the design of digital frequency selective FIR fillters using an FPA-based algorithm", Expert Systems with Applications, vol. 106, 2018.
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", 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.
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.
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", 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.
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.
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.
E
Bouix, S., M. Martin-Fernandez, L. Ungar, M. Nakamura, M-S. Koo, R. W. McCarley, and M. E. Shenton, "On evaluating brain tissue classifiers without a ground truth", Neuroimage, vol. 36, no. 4: Academic Press, pp. 1207–1224, 2007.
Tristán-Vega, A., F. Simmross-Wattenberg, E. Muñoz-Moreno, P. Casaseca-de-la-Higuera, and M. Martin-Fernandez, "On the estimation of joint probability density functions for multi-modal registration of medical images", Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB), vol. 26, Valladolid, Spain, Sociedad Española de Ingeniería Biomédica, pp. 13-16, 2008.

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