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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Detalles Bibliográficos
Autores principales: Nagasawa, Toshihiko, Tabuchi, Hitoshi, Masumoto, Hiroki, Morita, Shoji, Niki, Masanori, Ohara, Zaigen, Yoshizumi, Yuki, Mitamura, Yoshinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041547/
https://www.ncbi.nlm.nih.gov/pubmed/33884202
http://dx.doi.org/10.1155/2021/6651175

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041547/
https://www.ncbi.nlm.nih.gov/pubmed/33884202
http://dx.doi.org/10.1155/2021/6651175

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