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Classification of retinal vessels into arteries and veins for detection of hypertensive retinopathy

机译:将视网膜血管分为动脉和静脉以检测高血压性视网膜病变

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The damage to the retina of the eye caused by high blood pressure is known as hypertensive retinopathy (HR). The advancement in automatic retinal image analysis has made it possible to detect & diagnose this disease at an early stage. To indicate the presence and severity of Hypertensive Retinopathy, Arterio-Venous ratio (AVR) is an important measurement. For the calculation of AVR (the ratio of retinal arterioles to venuoles), classification of vessels into arteries and veins is an essential step. This paper proposes a novel technique for classifying the vessels into arteries and veins. The proposed system uses binary vessel mask and optic disc (OD) center localization to extract Region of Interest (ROI) around OD. Feature extraction modules extract a number of intensity based features followed by classification which classifies vessels as arteries and veins. The features are extracted by focusing on the visual difference between the arteries and veins in different color spaces. The proposed system is tested on a locally gather fundus image dataset. An accuracy of 81.3% is achieved.
机译:高血压对眼睛视网膜造成的损害称为高血压性视网膜病(HR)。自动化的视网膜图像分析技术的进步使在早期发现和诊断这种疾病成为可能。为了表明高血压性视网膜病的存在和严重程度,动静脉比率(AVR)是一项重要的测量指标。为了计算AVR(视网膜小动脉与小静脉的比率),将血管分类为动脉和静脉是必不可少的步骤。本文提出了一种将血管分类为动脉和静脉的新技术。拟议的系统使用二进制血管罩和光盘(OD)中心定位来提取OD周围的感兴趣区域(ROI)。特征提取模块提取许多基于强度的特征,然后进行分类,从而将血管分类为动脉和静脉。通过关注不同颜色空间中的动脉和静脉之间的视觉差异来提取特征。所提出的系统在本地收集的眼底图像数据集上进行了测试。达到81.3%的精度。

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