Cargando…
Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings
Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existing automated algorithms have mostly been developed from images acquired with high cost mydriatic retinal cameras and cannot be applied in the settings...
Autores principales: | Nunez do Rio, Joan M., Nderitu, Paul, Raman, Rajiv, Rajalakshmi, Ramachandran, Kim, Ramasamy, Rani, Padmaja K., Sivaprasad, Sobha, Bergeles, Christos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876892/ https://www.ncbi.nlm.nih.gov/pubmed/36697482 http://dx.doi.org/10.1038/s41598-023-28347-z |
Ejemplares similares
-
Deep learning for gradability classification of handheld, non-mydriatic retinal images
por: Nderitu, Paul, et al.
Publicado: (2021) -
Evaluating a Deep Learning Diabetic Retinopathy Grading System Developed on Mydriatic Retinal Images When Applied to Non-Mydriatic Community Screening
por: Nunez do Rio, Joan M., et al.
Publicado: (2022) -
Diabetic retinopathy screening guidelines in India: All India Ophthalmological Society diabetic retinopathy task force and Vitreoretinal Society of India Consensus Statement
por: Raman, Rajiv, et al.
Publicado: (2021) -
The ORNATE India project: Building research capacity and capability to tackle the burden of diabetic retinopathy-related blindness in India
por: Conroy, Dolores, et al.
Publicado: (2021) -
Deep Learning-Based Segmentation and Quantification of Retinal Capillary Non-Perfusion on Ultra-Wide-Field Retinal Fluorescein Angiography
por: Nunez do Rio, Joan M., et al.
Publicado: (2020)