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Núria Roé-Vellvé
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2020 – today
- 2020
- [j4]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello:
Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution. Integr. Comput. Aided Eng. 27(3): 233-251 (2020) - [j3]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, Rafael Marcos Luque Baena, Núria Roé-Vellvé:
Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting. Neurocomputing 398: 314-327 (2020) - [j2]Francisco Javier López-González, Jesús Silva-Rodríguez, José Paredes-Pacheco, Aida Niñerola-Baizán, Nikos Efthimiou, Carmen Martín-Martín, Alexis Moscoso, Álvaro Ruibal, Núria Roé-Vellvé, Pablo Aguiar:
Intensity normalization methods in brain FDG-PET quantification. NeuroImage 222: 117229 (2020) - [c3]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Lipika Deka:
Super-Resolution of 3D MRI Corrupted by Heavy Noise With the Median Filter Transform. ICIP 2020: 3015-3019
2010 – 2019
- 2019
- [j1]Francisco Javier López-González, José Paredes-Pacheco, Karl Thurnhofer-Hemsi, Carlos Rossi, Manuel Enciso, Daniel Toro-Flores, Belén Murcia-Casas, Antonio L. Gutiérrez-Cardo, Núria Roé-Vellvé:
QModeling: a Multiplatform, Easy-to-Use and Open-Source Toolbox for PET Kinetic Analysis. Neuroinformatics 17(1): 103-114 (2019) - [c2]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello:
Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. IWINAC (2) 2019: 287-296 - 2018
- [c1]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Enrique Domínguez, Miguel A. Molina-Cabello:
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks. IJCNN 2018: 1-8
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