Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images
Abstract Visually impaired and blind people due to diabetic retinopathy were 2.6 million in 2015 and estimated to be 3.2 million in 2020 globally. Though the incidence of diabetic retinopathy is expected to decrease for high-income countries, detection and treatment of it in the early stages are cru...
Enregistré dans:
Auteurs principaux: | Kangrok Oh, Hae Min Kang, Dawoon Leem, Hyungyu Lee, Kyoung Yul Seo, Sangchul Yoon |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/7dd1c9fa24774e6883b19d0d865f6e8a |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Telemedicine for diabetic retinopathy screening using an ultra-widefield fundus camera
par: Hussain N, et autres
Publié: (2017) -
Characteristics and application value of ultra-wide-field fundus auto-fluorescence in Stargardt disease
par: Zhi-Kun Zheng, et autres
Publié: (2021) -
Ultra-wide-field fluorescein angiography in diabetic retinopathy: a narrative review
par: Rabiolo A, et autres
Publié: (2017) -
Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
par: Jaakko Sahlsten, et autres
Publié: (2019) -
Wide-field fundus autofluorescence corresponds to visual fields in chorioretinitis patients
par: Seidensticker F, et autres
Publié: (2011)