基于视网膜彩色图像分析的微动脉瘤自动检测

Preeyaporn Yunuch, Noppadol Maneerat, D. Isarakorn, B. Pasaya, Ronakorn Panjaphongse, R. Varakulsiripunth
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引用次数: 7

摘要

本文通过分析视网膜图像的异常,提出了一种糖尿病视网膜病变症状自动诊断系统。开发了一种用于视网膜图像分析的数字图像处理系统,以帮助眼科医生识别糖尿病患者。利用眼科医生提供的视网膜图像,通过HSV、区域识别和偏心技术进行分析,将糖尿病视网膜病变症状与正常糖尿病患者区分开来。首先采用HSV法对颜色条进行评估,然后采用像素面积偏心技术对微动脉瘤(MAs)进行异常检测。实验结果与眼科医生的分析结果相比,准确率在93%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic microaneurysms detection through retinal color image analysis
This paper proposes an automatic system to diagnose the diabetic retinopathy symptom, which can cause a loss of vision by analysis the abnormality in retinal image. Digital image processing system is developed for the retinal image analysis which helps ophthalmologists to identify diabetic patients. The retinal images derived from ophthalmologists are used to analysis by using HSV, area identification and eccentricity techniques to distinguish diabetic retinopathy symptoms from normal diabetic patients. First color bar is evaluated by using HSV method and then using the eccentricity technique with area of pixel to find out the abnormality of Microaneurysms (MAs). The accuracy result of experiment is around 93% when compares to the analysis of ophthalmologists.
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