Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography

PURPOSE: The present study aimed to compare the accuracy of diabetic retinopathy (DR) staging with a deep convolutional neural network (DCNN) using two different types of fundus cameras and composite images. METHOD: The study included 491 ultra-wide-field fundus ophthalmoscopy and optical coherence...

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Detalhes bibliográficos
Publicado no:J Ophthalmol
Main Authors: Nagasawa, Toshihiko, Tabuchi, Hitoshi, Masumoto, Hiroki, Morita, Shoji, Niki, Masanori, Ohara, Zaigen, Yoshizumi, Yuki, Mitamura, Yoshinori
Formato: Artigo
Idioma:Inglês
Publicado em: Hindawi 2021
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8041547/
https://ncbi.nlm.nih.gov/pubmed/33884202
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2021/6651175
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