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

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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,… Click to show full abstract

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.

Keywords: optical coherence; tomography angiography; classification diabetic; objective classification; coherence tomography; classification

Journal Title: Biomedical optics express
Year Published: 2019

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