Application of Novel Software Algorithms to Spectral-Domain Optical Coherence Tomography for Automated Detection of Diabetic Retinopathy

Copyright 2016, SLACK Incorporated.

Bibliographische Detailangaben
Veröffentlicht in:Ophthalmic surgery, lasers & imaging retina. - 2013. - 47(2016), 5 vom: 01. Mai, Seite 410-7
1. Verfasser: Adhi, Mehreen (VerfasserIn)
Weitere Verfasser: Semy, Salim K, Stein, David W, Potter, Daniel M, Kuklinski, Walter S, Sleeper, Harry A, Duker, Jay S, Waheed, Nadia K
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:Ophthalmic surgery, lasers & imaging retina
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:Copyright 2016, SLACK Incorporated.
BACKGROUND AND OBJECTIVE: To present novel software algorithms applied to spectral-domain optical coherence tomography (SD-OCT) for automated detection of diabetic retinopathy (DR)
PATIENTS AND METHODS: Thirty-one diabetic patients (44 eyes) and 18 healthy, nondiabetic controls (20 eyes) who underwent volumetric SD-OCT imaging and fundus photography were retrospectively identified. A retina specialist independently graded DR stage. Trained automated software generated a retinal thickness score signifying macular edema and a cluster score signifying microaneurysms and/or hard exudates for each volumetric SD-OCT
RESULTS: Of 44 diabetic eyes, 38 had DR and six eyes did not have DR. Leave-one-out cross-validation using a linear discriminant at missed detection/false alarm ratio of 3.00 computed software sensitivity and specificity of 92% and 69%, respectively, for DR detection when compared to clinical assessment
CONCLUSION: Novel software algorithms applied to commercially available SD-OCT can successfully detect DR and may have potential as a viable screening tool for DR in future. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:410-417.]
Beschreibung:Date Completed 26.06.2017
Date Revised 01.12.2017
published: Print
Citation Status MEDLINE
ISSN:2325-8179
DOI:10.3928/23258160-20160419-03