A fast and fully automated system for glaucoma detection using color fundus photographs

This paper presents a low computationally intensive and memory efficient convolutional neural network (CNN)-based fully automated system for detection of glaucoma, a leading cause of irreversible blindness worldwide. Using color fundus photographs, the system detects glaucoma in two steps. In the fi...

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Detalles Bibliográficos
Autores principales: Saha, Sajib, Vignarajan, Janardhan, Frost, Shaun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611813/
https://www.ncbi.nlm.nih.gov/pubmed/37891238
http://dx.doi.org/10.1038/s41598-023-44473-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611813/
https://www.ncbi.nlm.nih.gov/pubmed/37891238
http://dx.doi.org/10.1038/s41598-023-44473-0

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