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

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

Content Provider	Scilit
Author	Coyner, Aaron S. Swan, Ryan Campbell, J. Peter Ostmo, Susan Brown, James M. Kalpathy-Cramer, Jayashree Kim, Sang Jin Jonas, Karyn E. Chan, R. V. Paul Chiang, Michael F. Sonmez, Kemal Horowitz, Jason Coki, Osode Eccles, Cheryl-Ann Sarna, Leora Orlin, Anton Berrocal, Audina Negron, Catherin Denser, Kimberly Cumming, Kristi Osentoski, Tammy Check, Tammy Zajechowski, Mary Lee, Thomas Kruger, Evan McGovern, Kathryn Simmons, Charles Murthy, Raghu Galvis, Sharon Rotter, Jerome Chen, Ida Li, Xiaohui Taylor, Kent Roll, Kaye Chang, Ken Beers, Andrew Erdogmus, Deniz Ioannidis, Stratis Martinez-Castellanos, Maria Ana Salinas-Longoria, Samantha Romero, Rafael Arriola, Andrea Olguin-Manriquez, Francisco Meraz-Gutierrez, Miroslava Dulanto-Reinoso, Carlos M. Montero-Mendoza, Cristina
Copyright Year	2019
Description	Journal: Ophthalmology Retina
Related Links	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6501831/pdf
Ending Page	450
Page Count	7
Starting Page	444
ISSN	24686530
e-ISSN	24686530
DOI	10.1016/j.oret.2019.01.015
Journal	Ophthalmology Retina
Issue Number	5
Volume Number	3
Language	English
Publisher	Elsevier BV
Publisher Date	2019-05-01
Access Restriction	Open
Subject Keyword	Journal: Ophthalmology Retina Retinal Fundus Images Based Image Analysis
Content Type	Text
Resource Type	Article
Subject	Ophthalmology

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