Publications

Export 15 results:
Author Title [ Type(Asc)] Year
Filters: First Letter Of Last Name is J  [Clear All Filters]
Journal Article
Sabzi, S., H. Javadikia, and J. I. Arribas, "A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value", Measurement, vol. 152, pp. 107298, 2020.
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", 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.
Javadikia, H., S. Sabzi, and J. I. Arribas, "An automatic and non-intrusive hybrid computer vision system for the estimation of peel thickness in Thomson orange", Spanish Journal of Agricultural Research, vol. 16, issue 4, pp. e0204, 2018.
Merino-Caviedes, S., L. Gutiérrez, J. Alfonso-Almazán, S. Sanz-Estébanez, L. Cordero-Grande, J. Quintanilla, J. Sánchez-González, M. Marina-Breysse, C. Galán-Arriola, D. Enríquez-Vázquez, et al., "Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy", Scientific Reports, vol. 11, 2021.
Pieciak, T., M. Afzali, F. Bogusz, S. Aja-Fernández, and D. K. Jones, "Q-space quantitative diffusion MRI measures using a stretched-exponential representation", arXiv, 2020.
Afzali, M., S. Aja-Fernández, and D. K. Jones, "Direction-averaged diffusion-weighted MRI signal using different axisymmetric B-tensor encoding schemes", Magnetic Resonance in Medicine, vol. n/a, 2020.
Aja-Fernández, S., A. Tristán-Vega, and D. K. Jones, "Apparent propagator anisotropy from single-shell diffusion MRI acquisitions", Magnetic Resonance in Medicine, vol. 85, issue 5, pp. 2869-2881, 2021.
Aja-Fernández, S., G. París, C. Martín-Martín, D. K. Jones, and AT. -Vega, "Anisotropy measure from three diffusion-encoding gradient directions", Magnetic Resonance Imaging, vol. 88, pp. 38–43, 2022.