publications

Publications

  • Mármol Rivera, J. A., Fernández-Rodríguez, J. D., Asenjo, B., & López-Rubio, E. (2025). Latent diffusion for arbitrary zoom MRI super-resolution. Expert Systems with Applications, 127970. https://doi.org/10.1016/j.eswa.2025.127970
  • Díaz Francés, J. Á., Fernández-Rodríguez, J. D., Thurnhofer-Hemsi, K., & López-Rubio, E. (2024). Semi-supervised semantic image segmentation by deep diffusion models and generative adversarial networks. International Journal of Neural Systems. https://doi.org/10.1142/s0129065724500576
  • Lima Junior, M. S. P. dos S., López-Rubio, E., Ortiz-de-Lazcano-Lobato, J. M., & Fernández-Rodríguez, J. D. (2025). Enhanced generation of automatically labelled image segmentation datasets by advanced style interpreter deep architectures. Pattern Recognition Letters. https://doi.org/10.1016/j.patrec.2025.04.021
  • Fernández-Rodríguez, A., López-Rubio, E., Torres-Salomón, P., Rodríguez-Capitán, J., Jiménez-Navarro, M., & Molina-Cabello, M. A. (2024). Enhancing echocardiography quality with diffusion neural models. In IWBBIO 2024. https://doi.org/10.1007/978-3-031-64636-2_13
  • Atencia-Jiménez, I., Balajee, A. S., Ruiz-Gómez, M. J., Sendra-Portero, F., Montoro, A., & Molina-Cabello, M. A. (2024). Neural network ensemble to detect dicentric chromosomes in metaphase images. Applied Sciences, 14(22), 10440. https://doi.org/10.3390/app142210440
  • Ruiz-Casado, J. L., Molina-Cabello, M. A., & Luque-Baena, R. M. (2024). Enhancing histopathological image classification performance through synthetic data generation with generative adversarial networks. Sensors, 24(12), 3777. https://doi.org/10.3390/s24123777
  • Jiménez-Partinen, A., Molina-Cabello, M. A., Thurnhofer-Hemsi, K., Palomo, E. J., Rodríguez-Capitán, J., Molina-Ramos, A. I., & Jiménez-Navarro, M. (2024). CADICA: A new dataset for coronary artery disease detection by using invasive coronary angiography. Expert Systems. https://doi.org/10.1111/exsy.13708
  • Jiménez-Partinen, A., Thurnhofer-Hemsi, K., Rodríguez-Capitán, J., Molina-Ramos, A. I., & Palomo, E. J. (2024). Coronary artery disease classification with different lesion degree ranges based on deep learning. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3401465
  • Nazzal, W., Thurnhofer-Hemsi, K., & López-Rubio, E. (2024). Improving medical image segmentation using test-time augmentation with MedSAM. Mathematics, 12(24), 4003. https://doi.org/10.3390/math12244003
  • García Aguilar, I., García-González, J., Medina, D., Luque Baena, R. M., Domínguez, E., & López-Rubio, E. (2023). Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size. Neurocomputing, 535, 127057. https://doi.org/10.1016/j.neucom.2023.127057
  • Aguilar-Castillo, M. J., Cabezudo-García, P., García-Martín, G., Lopez-Moreno, Y., Estivill-Torrús, G., Ciano-Petersen, N. L., Oliver-Martos, B., Narváez-Pelaez, M., & Serrano-Castro, P. J. (2024). A systematic review of the predictive and diagnostic uses of neuroinflammation biomarkers for epileptogenesis. International Journal of Molecular Sciences, 25(12), 6488. https://doi.org/10.3390/ijms25126488
  • Serrano-Castro, P. J., Rodríguez-Uranga, J. J., Cabezudo-García, P., García-Martín, G., Romero-Godoy, J., Estivill-Torrús, G., Ciano-Petersen, N. L., Oliver, B., Ortega-Pinazo, J., López-Moreno, Y., Aguilar-Castillo, M. J., Gutierrez-Cardo, A. L., Ramírez-García, T., Sanchez-Godoy, L., & Carreño, M. (2023). Cenobamate and clobazam combination as personalized medicine in autoimmune-associated epilepsy with anti-GAD65 antibodies. Neurology® Neuroimmunology & Neuroinflammation, 10(6), e200151. https://doi.org/10.1212/NXI.0000000000200151
  • Martínez-Marín, R. J., Reyes-Leiva, D., Nascimento, A., Muelas, N., Domínguez-González, C., Paradas, C., Olivé, M., García-Romero, M., Pascual-Pascual, S. I., Grau, J. M., Barba-Romero, M. A., Gómez-Caravaca, M. T., de Las Heras, J., Casquero, P., Mendoza, M. D., de León, J. C., Gutierrez, A., Morís, G.,García-Martín, G.., … Díaz-Manera, J. (2024). Description of clinical and genetic features of 122 patients included in the Spanish Pompe registry. Neuromuscular Disorders, 34, 1–8. https://doi.org/10.1016/j.nmd.2023.10.001
  • Serrano-Castro, P. J., Ramírez-García, T., Cabezudo-García, P., García-Martín, G., & De La Parra, J. (2024). Effect of cenobamate on cognition in patients with drug-resistant epilepsy with focal onset seizures: An exploratory study. CNS Drugs, 38(2), 141–151. https://doi.org/10.1007/s40263-024-01063-6
  • Ocaña-Tienda, B., Pérez-Beteta, J., Romero-Rosales, J. A., Asenjo, B., Ortiz de Mendivil, A., Pérez Romasanta, L. A., Albillo Labarra, J. D., Nagib, F., Vidal Denis, M., Luque, B., Arana, E., & Pérez-García, V. M. (2024). Volumetric analysis: Rethinking brain metastases response assessment. Neuro-Oncology Advances, 6(1), vdad161. https://doi.org/10.1093/noajnl/vdad161
  • Ocaña-Tienda, B., Pérez-Beteta, J., Jiménez-Sánchez, J., Molina-García, D., Ortiz de Mendivil, A., Asenjo, B., Albillo, D., Pérez-Romasanta, L. A., Valiente, M., Zhu, L., García-Gómez, P., González-Del Portillo, E., Llorente, M., Carballo, N., Arana, E., & Pérez-García, V. M. (2023). Growth exponents reflect evolutionary processes and treatment response in brain metastases. NPJ Systems Biology and Applications, 9(1), 28. https://doi.org/10.1038/s41540-023-00298-1
  • Ocaña-Tienda, B., Pérez-Beteta, J., Villanueva-García, J. D., Romero-Rosales, J. A., Molina-García, D., Suter, Y., Asenjo, B., Albillo, D., Ortiz de Mendivil, A., Pérez-Romasanta, L. A., González-Del Portillo, E., Llorente, M., Carballo, N., Nagib-Raya, F., Vidal-Denis, M., Luque, B., Reyes, M., Arana, E., & Pérez-García, V. M. (2023). A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data. Scientific Data, 10, 553. https://doi.org/10.1038/s41597-023-02123-0
  • Ocaña-Tienda, B., Pérez-Beteta, J., Ortiz de Mendivil, A., Asenjo, B., Albillo, D., Pérez-Romasanta, L. A., LLorente, M., Carballo, N., Arana, E., & Pérez-García, V. M. (2024). Morphological MRI features as prognostic indicators in brain metastases. Cancer Imaging, 24(1), 26. https://doi.org/10.1186/s40644-024-00753-0

Conferences

  • Terán-Pineda, D., Thurnhofer-Hemsi, K., Fernández-Rodríguez, J. D., & Domínguez, E. (2024). Deep learning models for gait event prediction. In Proceedings of the International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn60899.2024.10650446
  • Fernández-Rodríguez, J. D., Benito-Picazo, J., García-Aguilar, I., & López-Rubio, E. (2024). Automated semantic labelling of images generated with deep diffusion probabilistic models. In SOCO 2024: Soft computing models in industrial and environmental applications. https://doi.org/10.1007/978-3-031-75013-7_4
  • Tell-González, G., López-Rubio, E., Benítez-Rochel, R., & Molina-Cabello, M. A. (2024). Early breast cancer detection by automated analysis of mammograms with deep convolutional networks. In SOCO 2024: Soft Computing Models in Industrial and Environmental Applications. https://doi.org/10.1007/978-3-031-75010-6_5
  • Jiménez-Partinen, A., Palomo, E. J., Thurnhofer-Hemsi, K., Rodríguez-Capitán, J., & Molina-Ramos, A. I. (2024). Deep learning-based classification of invasive coronary angiographies with different patch-generation techniques. In IWINAC 2024. https://doi.org/10.1007/978-3-031-61137-7_12
  • Rey-Blanes, A., & Domínguez, E. (2024). Applying deep learning based super-resolution to knee imaging. In AIiH 2024. https://doi.org/10.1007/978-3-031-67285-9_6
  • García Aguilar, I., Zavoiko, R., Fernández Rodríguez, J. D., Luque Baena, R. M., & López-Rubio, E. (2024). Enhanced cellular detection using convolutional neural networks and sliding window super-resolution inference. In IWINAC 2024 (Vol. 2, pp. 44–54).
  • García Aguilar, I., Jafri, S. A. H., Elizondo, D. A., Calderón Ramírez, S., Greenfield, S., & Luque-Baena, R. M. (2024). Enhancing object segmentation via few-shot learning with limited annotated data. In SOCO 2024 (Vol. 2, pp. 32–41).

Other Publications

  • García Aguilar, I., Galeano-Brajones, J., Luna-Valero, F., Carmona-Murillo, J., Fernández-Rodríguez, J. D., & Luque-Baena, R. M. (2024). Prediction of optimal locations for 5G base stations in urban environments using neural networks and satellite image analysis. In IWINAC 2024 (Vol. 2, pp. 33–43).
  • Surribas-Sayago, G., Fernández-Rodríguez, J. D., & Domínguez, E. (2024). Advancing photovoltaic forecasting with neural networks: Integrating N-Beats and sequential models with Fourier analysis. In IBERAMIA 2024. https://doi.org/10.1007/978-3-031-80366-6_24
  • Molina-Pinel, D., García-González, J., Domínguez, E., & López-Rubio, E. (2024). Novel positional encoding methods for neural rendering. In SOCO 2024. https://doi.org/10.1007/978-3-031-75010-6_3
  • Fernández-Rodríguez, A., Fernández-Rodríguez, J. D., López-Rubio, E., & Molina-Cabello, M. A. (2024). Mitigating motion blur in images using encoding generative adversarial network. In Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU). https://doi.org/10.5281/zenodo.15149423
  • Tell-González, G., Fernández-Rodríguez, J. D., Molina-Cabello, M. A., Benítez-Rochel, R., & López-Rubio, E. (2024). Mitigating Carlini & Wagner attacks with encoding generative adversarial network. In Proceedings of CAEPIA 2024. ISBN: 978-84-09-62724-0
  • Fernández-Rodríguez, J. D., Carmona-Martínez, P., Benítez Rochel, R., Molina-Cabello, M. A., & López-Rubio, E. (2024). Unsupervised detection of incoming and outgoing traffic flows in video sequences. In IWINAC 2024: Bioinspired computation and applications in image processing. https://doi.org/10.1007/978-3-031-61137-7_1
  • Molina-Cabello, M. A., Serrano-Angulo, J., Benito-Picazo, J., & Thurnhofer-Hemsi, K. (2024). Toward questionnaire complexity reduction by decreasing the questions. Applied Sciences, 15(2), 841. https://doi.org/10.3390/app15020841
  • Khan, N., Elizondo, D., Deka, L., & Molina-Cabello, M. A. (2024). Natural language processing tools and workflows for improving research processes. Applied Sciences, 14(24), 11731. https://doi.org/10.3390/app142411731
  • Rodríguez-Rodríguez, J. A., López-Rubio, E., Ángel Ruiz, J. A., & Molina-Cabello, M. A. (2024). The impact of noise and brightness on object detection methods. Sensors, 24(3), 821. https://doi.org/10.3390/s24030821
  • Molina-Cabello, M. A., Serrano-Angulo, J., Benito-Picazo, J., & Thurnhofer-Hemsi, K. (2024). Grades and learning styles: New software for analyzing correlations in a longitudinal study across different branches of knowledge and years. Applied Sciences, 14(24), 11941. https://doi.org/10.3390/app142411941