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Biomed Opt Express. 2019 Apr 22;10(5):2493-2503. doi: 10.1364/BOE.10.002493. eCollection 2019 May 1.

Fully automated geometric feature analysis in optical coherence tomography angiography for objective classification of diabetic retinopathy.

Le D1,2, Alam M1,2, Miao BA3, Lim JI4, Yao X1,4.

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Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.
These authors contributed equally to this work.
Benet Academy, Lisle, IL, 60532, USA.
Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA.


This study is to establish quantitative features of vascular geometry in optical coherence tomography angiography (OCTA) and validate them for the objective classification of diabetic retinopathy (DR). Six geometric features, including total vessel branching angle (VBA: θ), child branching angles (CBAs: α1 and α2), vessel branching coefficient (VBC), and children-to-parent vessel width ratios (VWR1 and VWR2), were automatically derived from each vessel branch in OCTA. Comparative analysis of heathy control, diabetes with no DR (NoDR), and non-proliferative DR (NPDR) was conducted. Our study reveals four quantitative OCTA features to produce robust DR detection and staging classification: (ANOVA, P<0.05), VBA, CBA1, VBC, and VWR1.

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