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

Author:

Coyner Aaron S.ORCID,Swan RyanORCID,Campbell J. Peter,Ostmo Susan,Brown James M.ORCID,Kalpathy-Cramer JayashreeORCID,Kim Sang Jin,Jonas Karyn E.ORCID,Chan R.V. PaulORCID,Chiang Michael F.,Chiang Michael F.,Ostmo Susan,Kim Sang Jin,Sonmez Kemal,Campbell J. Peter,Chan R. V. Paul,Jonas Karyn,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,Kalpathy-Cramer Jayashree,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

Funder

National Institutes of Health

Research to Prevent Blindness

Publisher

Elsevier BV

Subject

Ophthalmology

Reference38 articles.

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2. Expert diagnosis of plus disease in retinopathy of prematurity from computer-based image analysis;Campbell;JAMA Ophthalmol,2016

3. Quantitative brain magnetic resonance imaging in attention-deficit hyperactivity disorder;Castellanos;Arch Gen Psychiatry,1996

4. Image analysis for retinopathy of prematurity: where are we headed?;Chiang;J AAPOS,2012

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