Automated Analysis of Retinal Images for Detection of Referable Diabetic Retinopathy

Michael D. Abràmoff; James C. Folk; Dennis P. Han; Jonathan D. Walker; David F. Williams; Stephen R. Russell; Pascale Massin; Béatrice Cochener; Philippe Gain; Li Tang; Mathieu Lamard; Daniela C. Moga; Gwenolé Quellec; Meindert Niemeijer

doi:10.1001/jamaophthalmol.2013.1743

Abstract

The IDP has high sensitivity and specificity to detect RDR. Computer analysis of retinal photographs for DR and automated detection of RDR can be implemented safely into the DR screening pipeline, potentially improving access to screening and health care productivity and reducing visual loss through early treatment.

Keywords

MedicineDiabetic retinopathyReceiver operating characteristicRetinalRetinopathyOphthalmologyMacular edemaOptometryDiabetes mellitusInternal medicine

Affiliated Institutions

University of Iowa US

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Publication Info

Year: 2013
Type: article
Volume: 131
Issue: 3
Pages: 351-351
Citations: 425
Access: Closed

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APA Style

                            
                                
                                    Michael D. Abràmoff, 
                                
                                    James C. Folk, 
                                
                                    Dennis P. Han
                                
                                et al.
                            
                            (2013). 
                            Automated Analysis of Retinal Images for Detection of Referable Diabetic Retinopathy. 
                            JAMA Ophthalmology
                            , 131
                            (3)
                            , 351-351.
                            https://doi.org/10.1001/jamaophthalmol.2013.1743
                        

Identifiers

DOI: 10.1001/jamaophthalmol.2013.1743