IMR Press / FBE / Volume 10 / Issue 2 / DOI: 10.2741/E817

Frontiers in Bioscience-Elite (FBE) is published by IMR Press from Volume 13 Issue 2 (2021). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on as a courtesy and upon agreement with Frontiers in Bioscience.


An automated approach for early detection of diabetic retinopathy using SD-OCT images

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1 Department of Bioengineering, University of Louisville, 423 Lutz Hall, Louisville, KY, USA
2 Uveitis and Retina Fellow, Consultores Oftalmologicos, Hospital fernandez, Buenos Aires, Argentina
3 Department of Ophthalmology and Visual Sciences, University of Massachusetts Medical School, Worcester, MA, USA

*Author to whom correspondence should be addressed.

Front. Biosci. (Elite Ed) 2018, 10(2), 197–207;
Published: 1 January 2018

This study was to demonstrate the feasibility of an automatic approach for early detection of diabetic retinopathy (DR) from SD-OCT images. These scans were prospectively collected from 200 subjects through the fovea then were automatically segmented, into 12 layers. Each layer was characterized by its thickness, tortuosity, and normalized reflectivity. 26 diabetic patients, without DR changes visible by funduscopic examination, were matched with 26 controls, according to age and sex, for purposes of statistical analysis using mixed effects ANOVA. The INL was narrower in diabetes (p = 0.14), while the NFL (p = 0.04) and IZ (p = 0.34) were thicker. Tortuosity of layers NFL through the OPL was greater in diabetes (all p < 0.1), while significantly greater normalized reflectivity was observed in the MZ and OPR (both p < 0.01) as well as ELM and IZ (both p < 0.5). A novel automated method enables to provide quantitative analysis of the changes in each layer of the retina that occur with diabetes. In turn, carries the promise to a reliable non-invasive diagnostic tool for early detection of DR.

Spectral Domain Optical Coherence Tomography
Retinal Segmentation
Diabetic Retinopathy
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