糖尿病黄斑病变严重程度的自动分级

P. Siddalingaswamy, K. G. Prabhu
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引用次数: 56

摘要

糖尿病性黄斑病变是由视网膜病变引起的不可逆视力丧失的主要原因,占世界糖尿病人口的10%。强制性的大规模筛查有助于在早期发现黄斑病变,降低严重视力丧失的风险。在本文中,我们提出了一个基于计算机的系统,用于糖尿病黄斑病变严重程度的自动检测和分级,无需人工干预。自动检测视盘,利用视盘的位置和直径分别检测中央凹和标记黄斑区。接下来,使用聚类和数学形态学技术检测硬渗出物。根据黄斑区渗出物的位置,将黄斑病变的严重程度分为轻度、中度和重度。该方法对148张视网膜图像中黄斑病变分期的检测灵敏度为95.6%,特异度为96.15%,与人类专家的检测结果相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic grading of diabetic maculopathy severity levels
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.
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