Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

PURPOSE: Accurate image-based ophthalmic diagnosis relies on clarity of fundus images. This has important implications for the quality of ophthalmic diagnoses, and for emerging methods such as telemedicine and computer-based image analysis. The purpose of this study was to implement a deep convoluti...

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Detalhes bibliográficos
Publicado no:Ophthalmol Retina
Main Authors: Coyner, Aaron S., Swan, Ryan, Campbell, J. Peter, Ostmo, Susan, Brown, James M., Kalpathy-Cramer, Jayashree, Jin Kim, Sang, Jonas, Karyn E., Chan, R.V. Paul, Chiang, Michael F.
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6501831/
https://ncbi.nlm.nih.gov/pubmed/31044738
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.oret.2019.01.015
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