Automated Segmentation of Hard Exudates Using Dynamic Thresholding to Detect Diabetic Retinopathy in Retinal Photographs
Automated Segmentation of Hard Exudates Using Dynamic Thresholding to Detect Diabetic Retinopathy in Retinal Photographs
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使用动态阈值自动分割硬渗出物以检测视网膜照片中的糖尿病视网膜病变
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发表时间：
2016
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通讯作者：
Muhammad Zubair
中科院分区：
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作者：
Muhammad Zubair
视网膜图像被眼科医生用于不同视网膜疾病的临床分析和诊断。被称为糖尿病视网膜病变（DR）的眼部疾病是导致眼睛视网膜中的微血管变化的视网膜疾病。硬渗出物（HE）是一种视网膜病变，在彩色眼底照片中可以看到明亮的黄色斑点，在无红色眼底图像中可以看到明亮的白色斑点。本文的目的是提出一种自动化的技术，用于识别HE，以帮助DR的诊断。所提出的方法使用动态阈值分割HE后，计算输入视网膜图像的强度为基础的参数。在对渗出物进行分割之前，使用平均和形态学操作从图像中去除视盘（OD）。对MESSIDOR数据库中的1200幅HE图像进行分割，其敏感性为98.73%，特异性为98.25%，准确性为97.62%。与现有技术相比，所提出的自动化技术具有合理的准确性，可以用作值得信赖的临床诊断工具。
Retinal images are in use by ophthalmologists for the clinical analysis and diagnosis of different retinal diseases. The ocular disease known as Diabetic Retinopathy (DR) is a retinal disease that causes microvascular changes in the eye retina. Hard Exudates (HE) a retinal lesion can be seen as bright yellowish spots in colored fundus photograph and as bright white blobs in red free fundus image. The aim of this paper is to propose an automated technique for the identification of HE to help in the diagnosis of DR. The proposed method use dynamic thresholding for the segmentation of HE after calculating intensity based parameters of the input retinal image. Before the segmentation of exudates the Optic Disc (OD) is removed from the image using averaging and morphological operations. A sensitivity of 98.73%, specificity of 98.25% and accuracy 97.62% for HE segmentation is achieved respectively on 1200 images from publically available database MESSIDOR. Compared with the state of art, the proposed automated technique has a reasonable accuracy and can be used as a trustworthy clinical diagnostic tool.