Cargando…
Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19
One of the main challenges in times of sanitary emergency is to quickly develop computer aided diagnosis systems with a limited number of available samples due to the novelty, complexity of the case and the urgency of its implementation. This is the case during the current pandemic of COVID-19. This...
Autores principales: | Vidal, Plácido L., de Moura, Joaquim, Novo, Jorge, Ortega, Marcos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879025/ https://www.ncbi.nlm.nih.gov/pubmed/33612998 http://dx.doi.org/10.1016/j.eswa.2021.114677 |
Ejemplares similares
-
Data augmentation approaches using cycle-consistent adversarial networks for improving COVID-19 screening in portable chest X-ray images
por: Morís, Daniel Iglesias, et al.
Publicado: (2021) -
Fully automatic deep convolutional approaches for the analysis of COVID-19 using chest X-ray images
por: de Moura, Joaquim, et al.
Publicado: (2022) -
Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?
por: Álvarez-Rodríguez, Lorena, et al.
Publicado: (2022) -
Multivendor fully automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images
por: Vidal, Plácido, et al.
Publicado: (2023) -
Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning
por: Gende, Mateo, et al.
Publicado: (2023)