The goal was to characterize retinal vasculature by quantitative analysis of arteriole-to-venule (A/V) ratio and vessel density in fundus photos taken with the PanOptic iExaminer System. The PanOptic ophthalmoscope equipped with a smartphone was used to acquire fundus photos centered on the optic nerve head. Two fundus photos of a total of 19 eyes from 10 subjects were imaged. Retinal vessels were analyzed to obtain the A/V ratio. In addition, the vessel tree was extracted using deep learning U-NET, and vessel density was processed by the percentage of pixels within vessels over the entire image. All images were successfully processed for the A/V ratio and vessel density. There was no significant difference of averaged A/V ratio between the first (0.77 ± 0.09) and second (0.77 ± 0.10) measurements (P = 0.53). There was no significant difference of averaged vessel density (%) between the first (6.11 ± 1.39) and second (6.12 ± 1.40) measurements (P = 0.85). Quantitative analysis of the retinal vasculature was feasible in fundus photos taken using the PanOptic ophthalmoscope. The device appears to provide sufficient image quality for analyzing A/V ratio and vessel density with the benefit of portability, easy data transferring, and low cost of the device, which could be used for pre-clinical screening of systemic, cerebral and ocular diseases.

中文翻译：

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使用 PanOptic iExaminer 系统表征眼底照片中的视网膜脉管系统。


目标是通过对 PanOptic iExaminer 系统拍摄的眼底照片中的小动脉与小静脉 (A/V) 比率和血管密度进行定量分析来表征视网膜血管系统。使用配备智能手机的 PanOptic 检眼镜来获取以视神经乳头为中心的眼底照片。拍摄了 10 名受试者总共 19 只眼睛的两张眼底照片。分析视网膜血管以获得 A/V 比。此外，使用深度学习U-NET提取血管树，并通过血管内像素占整个图像的百分比来处理血管密度。所有图像均已成功处理 A/V 比和血管密度。第一次 (0.77 ± 0.09) 和第二次 (0.77 ± 0.10) 测量之间的平均 A/V 比没有显着差异 (P = 0.53)。第一次 (6.11 ± 1.39) 和第二次 (6.12 ± 1.40) 测量之间的平均血管密度 (%) 没有显着差异 (P = 0.85)。在使用 PanOptic 检眼镜拍摄的眼底照片中，对视网膜血管系统进行定量分析是可行的。该设备似乎可以为分析 A/V 比和血管密度提供足够的图像质量，并且具有便携性、数据传输方便和设备成本低的优点，可用于全身、脑和眼部疾病的临床前筛查。