Structured Abstract PURPOSE To develop a robust, sensitive, and fully automatic algorithm to quantify diabetes related capillary dropout using optical coherence tomography (OCT) angiography (OCTA). METHODS A 1050 nm wavelength, 400 kHz A-scan rate swept-source OCT prototype was used to perform volumetric OCTA imaging over 3 mm × 3 mm fields in normal controls (n = 5), patients with diabetes without diabetic retinopathy (DR) (n = 7), patients with non-proliferative diabetic retinopathy (NPDR) (n = 9), and patients with proliferative diabetic retinopathy (PDR) (n = 5); for each patient, one eye was imaged. A fully automatic algorithm to quantify intercapillary areas was developed. RESULTS Of the 26 evaluated eyes, the segmentation was successful in 22 eyes (85%). The mean values of the 10 and 20 largest intercapillary areas, either including or excluding the foveal avascular zone, showed a consistent trend of increasing size from normal control eyes, to eyes with diabetic retinopathy but without DR, to NPDR eyes, and finally, to PDR eyes. CONCLUSIONS OCTA based screening and monitoring of DR patients is critically dependent on automated vessel analysis. The presented algorithm was able to automatically extract an intercapillary area based metric in patients having various stages of DR. Intercapillary area based approaches are likely more sensitive to early stage capillary dropout than vascular density based methods.