A Deep Learning Algorithm for Classifying Diabetic Retinopathy Using Optical Coherence Tomography Angiography

PURPOSE: To develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolutional neural network (CNN) and to verify the feasibility of the system. METHODS: In this retrospective cross-sectional study, a total of 918 data sets...

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Detalles Bibliográficos
Autores principales: Ryu, Gahyung, Lee, Kyungmin, Park, Donggeun, Kim, Inhye, Park, Sang Hyun, Sagong, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899862/
https://www.ncbi.nlm.nih.gov/pubmed/35703566
http://dx.doi.org/10.1167/tvst.11.2.39

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899862/
https://www.ncbi.nlm.nih.gov/pubmed/35703566
http://dx.doi.org/10.1167/tvst.11.2.39

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