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Automatic grading of diabetic maculopathy severity levels

机译:糖尿病性黄斑病变严重程度的自动分级

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摘要

Diabetic maculopathy is the major cause of irreversible vision loss due to retinopathy and is found in 10% of the world diabetic population. Compulsory mass screening will help to identify the maculopathy at early stage and reduce the risk of severe vision loss. In this paper, we present a computer based system for automatic detection and grading of diabetic maculopathy severity level without manual intervention. The optic disc is detected automatically and its location and diameter is used to detect fovea and to mark the macular region respectively. Next, hard exudates are detected using clustering and mathematical morphological techniques. Based on the location of exudates in marked macular region the severity level of maculopathy is classified into mild, moderate and severe. The method achieves a sensitivity of 95.6% and specificity of 96.15% with 148 retinal images for detecting maculopathy stages in fundus images as comparable to that of human expert.
机译:糖尿病性黄斑病变是由于视网膜病变导致不可逆视力丧失的主要原因,在全世界10%的糖尿病患者中发现。强制性质量筛查将有助于早期识别黄斑病,并降低严重视力丧失的风险。在本文中,我们提出了一种无需人工干预即可自动检测和分级糖尿病性黄斑病变严重程度的基于计算机的系统。自动检测视盘,并使用其位置和直径分别检测中央凹并标记黄斑区域。接下来,使用聚类和数学形态学技术检测硬质渗出液。根据渗出液在明显的黄斑区域中的位置,将黄斑病变的严重程度分为轻度,中度和重度。该方法通过1​​48张视网膜图像检测眼底图像中的黄斑病变阶段,与人类专家相比具有95.6%的灵敏度和96.15%的特异性。

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