Núria Roé-Vellvé

Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks

Miguel A. Molina-Cabello, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Super-Resolution of 3D MRI Corrupted by Heavy Noise With the Median Filter Transform

Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, Núria Roé-Vellvé, 2020, 2020 IEEE International Conference on Image Processing (ICIP).

QModeling: a Multiplatform, Easy-to-Use and Open-Source Toolbox for PET Kinetic Analysis

Karl Thurnhofer-Hemsi, Manuel Enciso, Núria Roé-Vellvé, 2018, Neuroinformatics.

Intensity normalization methods in brain FDG-PET quantification

Pablo Aguiar, Núria Roé-Vellvé, Nikos Efthimiou, 2020, NeuroImage.

Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting

Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, Enrique Domínguez, 2020, Neurocomputing.

Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images

Miguel A. Molina-Cabello, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, 2019, IWINAC.

Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution

Miguel A. Molina-Cabello, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi, 2020, Integr. Comput. Aided Eng..