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Diabetic Retinopathy Detection by Extracting Area and Number of Microaneurysm from Colour Fundus Image

机译:通过从彩色眼底图像中提取微动脉瘤的面积和数目来检测糖尿病性视网膜病变

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This paper presents an improved diabetic retinopathy detection scheme by extracting accurate area and ate number of microaneurysm from color fundus images. Regular screening of eye is crucial for detection and dealing with diabetic retinopathy. Diabetic retinopathy (DR) is an eye disease which occurs due to damage of retina as a result of long illness of diabetic mellitus. Microaneurysms (MA) are tiny red spots on retina, shaped by inflating out of fragile part of the blood vessels. The recognition of MA at primary stage is very crucial and it is the first step in inhibiting DR. A variety of methods have been proposed for detection and diagnosis of DR. In this paper, there are two features namely; number and area of MA have been determined. Initially, pre-processing techniques like green channel extraction, histogram equalization and morphological process have been used. For detection of microaneurysms, principal component analysis (PCA), contrast limited adaptive histogram equalization (CLAHE), morphological process, averaging filtering have been used. Classification of DR has been done by linear Support vector machine (SVM). The sensitivity and specificity of DR detection system are observed as 96% and 92% respectively.
机译:通过从彩色眼底图像中提取准确的面积和微动脉瘤的数量,提出了一种改进的糖尿病视网膜病变检测方案。定期检查眼睛对于发现和治疗糖尿病性视网膜病至关重要。糖尿病性视网膜病(DR)是一种眼病,由于长期患有糖尿病导致视网膜受损而发生。微动脉瘤(MA)是视网膜上的微小红色斑点,其形状是通过扩张脆弱血管的形状而形成的。在初级阶段对MA的识别非常关键,这是抑制DR的第一步。已经提出了多种用于DR的检测和诊断的方法。本文具有两个特征,即: MA的数量和面积已确定。最初,已经使用了诸如绿色通道提取,直方图均衡化和形态学处理之类的预处理技术。对于微动脉瘤的检测,主成分分析(PCA),对比度受限的自适应直方图均衡化(CLAHE),形态过程,平均滤波已被使用。 DR的分类已通过线性支持向量机(SVM)进行。 DR检测系统的灵敏度和特异性分别为96%和92%。

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