Publicaciones
Publicaciones Asociadas
Este laboratorio virtual implementa los hallazgos descritos en los siguientes estudios.
Artículos y Conferencias
- Beyond Binary Classification: A Pilot Study of Imaging-Derived Glioma Severity Modeling Using T1-Weighted and Diffusion MRI Radiomics
Franco, P., Montalba, C., Caulier-Cisterna, R., Espinoza, I., Cornejo, M. D., Torres, F., Bennett, C., Chabert, S., Salas, R. MAGMA (2026)
Leer Artículo Código en GitHub - Feasibility of Tumor-Masked Structural Connectomics and Explainable Machine Learning for Assessing White Matter Disruption in Gliomas: A Pilot Study
Montalba, C., Espinoza, I., Cornejo, M. D., Torres, F., Bennett, C., Chabert, S., Salas, R., & Franco, P. ESMRMB (2026)
Lightning Talk (Abstract #54477) Código en GitHub
Figura 1: Reconstrucción tridimensional mediante tensores de difusión (DTI) y tractografía de fibras de sustancia blanca en un paciente, junto a la segmentación del glioma (en rojo). - Radiomic Glioma Grading Using T1-weighted MRI vs. Diffusion Tensor Metrics: A Proof-of-Concept Comparative Analysis with Explainable Machine Learning
Franco, P., Montalba, C. B., Caulier-Cisterna, R., Espinoza, I., Cornejo, M. D., Torres, F., Bennett, C., Chabert, S., Salas, R. ICPRS (2025)
Ver en IEEE Xplore Código en GitHub - Explainable machine learning models for radiomic-based assessment of glioma severity using multiparametric MRI (Abstract #215)
Franco, P., Montalba, C., Caulier-Cisterna, R., Espinoza, I., Bennet, C., Torres, F., Chabert, S., & Salas, R. ESMRMB (2025)
Ver en Springer
Citas (BibTeX)
Si utilizas este código o los hallazgos para tu investigación, por favor cita los siguientes trabajos:
Haz clic aquí para desplegar las citas en formato BibTeX
@article{Franco2026Glioma,
title={Beyond Binary Classification: A Pilot Study of Imaging-Derived Glioma Severity Modeling Using T1-Weighted and Diffusion MRI Radiomics},
author={Franco, Pamela and Montalba, Cristian and Caulier-Cisterna, Raúl and Espinoza, Ignacio and Cornejo, M. Daniela and others},
journal={Magnetic Resonance Materials in Physics, Biology and Medicine (MAGMA)},
year={2026},
doi={10.1007/s10334-026-01346-7}
}
@inproceedings{montalba2026feasibility,
title={Feasibility of Tumor-Masked Structural Connectomics and Explainable Machine Learning for Assessing White Matter Disruption in Gliomas: A Pilot Study},
author={Montalba, Cristian and Espinoza, Ignacio and Cornejo, M. Daniela and Torres, Francisco and Bennett, Carlos and Chabert, Steren and Salas, Rodrigo and Franco, Pamela},
booktitle={Proceedings of the 42nd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB 2026)},
year={2026},
address={Girona, Spain},
note={Lightning Talk D24 - LTD2-3, Session PG185, Abstract \#54477}
}
@inproceedings{Franco2025ICPRS,
title={Radiomic Glioma Grading Using T1-weighted MRI vs. Diffusion Tensor Metrics: A Proof-of-Concept Comparative Analysis with Explainable Machine Learning},
author={Franco, Pamela and Montalba, Cristian Beethet and Caulier-Cisterna, Raúl and Espinoza, Ignacio and Cornejo, M. Daniela and others},
booktitle={2025 15th IEEE International Conference on Pattern Recognition Systems (ICPRS)},
pages={1--7},
year={2025},
publisher={IEEE},
doi={10.1109/ICPRS64124.2025.11302837}
}
@article{Franco2025ESMRMB,
title={Explainable machine learning models for radiomic-based assessment of glioma severity using multiparametric MRI (Abstract \#215)},
author={Franco, Pamela and Montalba, Cristian and Caulier-Cisterna, Raúl and Espinoza, Ignacio and Bennet, Carlos and Torres, Francisco and Chabert, Steren and Salas, Rodrigo},
journal={Magnetic Resonance Materials in Physics, Biology and Medicine},
volume={38},
number={1},
pages={201--202},
year={2025},
publisher={Springer},
doi={10.1007/s10334-025-01278-8}
}