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Detection of retinal blood vessels and reduction of false microaneurysms for diagnosis of diabetic retinopathy

机译:检测视网膜血管并减少假性微动脉瘤以诊断糖尿病性视网膜病

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摘要

Diabetic retinopathy affects the human eye and causes the blindness. For the efficient diagnosis of retinopathy accurate measurement (true vessel structure) of vessel diameter is required for estimating the types of vessels. True approximation of total number of microaneurysms is required for estimating the stages of diabetic retinopathy. This work presents an automated system for detection and prediction of diabetic retinopathy severity (based on stages) on retinal fundus image. The algorithm starts by preprocessing the image by spatial low pass filter and for feature extraction optimized Gabor filter is used. Further integrated approach of morphological operation erosion and extended minima transform is used for estimating true vessels structure. An approach of Skelotonization is also proposed for estimation of true vessel structure. Euclidian distance measure approach is applied for calculating the diameter of vessels at four discrete points in filtered image. Stages of diabetic retinopathy are classified based on calculated diameter.
机译:糖尿病性视网膜病会影响人眼并导致失明。为了有效诊断视网膜病变,需要准确测量血管直径(真实血管结构)以估计血管类型。估计糖尿病性视网膜病变的阶段需要微动脉瘤总数的真实近似值。这项工作提出了一种自动系统,用于在视网膜眼底图像上检测和预测糖尿病性视网膜病变的严重程度(基于分期)。该算法首先通过空间低通滤波器对图像进行预处理,然后针对特征提取使用优化的Gabor滤波器。形态操作侵蚀和扩展的最小变换的进一步集成方法用于估计真实的血管结构。还提出了骨架加速的方法来估计真实的血管结构。欧氏距离测量方法用于计算滤波图像中四个离散点处的血管直径。糖尿病性视网膜病变的阶段根据计算出的直径进行分类。

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