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An adaptive threshold based algorithm for detection of red lesions of diabetic retinopathy in a fundus image

机译:基于自适应阈值基于阈值的基于眼底图像中糖尿病视网膜病变的红色病变的算法

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The paper proposes an algorithm for detection of Red Lesions present in a fundus image of an eye. Red Lesions include Micro-aneurysms and Hemorrhages, which are the symptoms of Diabetic Retinopathy, a widespread eye disease which affects almost every diabetic patient at some point of the patients life. The paper presents an adaptive method to detect the red lesions present in an image. The proposed method will estimate the upper threshold and the lower threshold of the red lesions for the given fundus image individually based on local image information. The significance of the adaptive nature of this proposed algorithm is that fundus images acquired from different cameras may vary in quality and resolution. As a result the intensity of red lesions may vary from image to image. Since, the intensity of red lesions is similar to that of the blood vessels for a specific image, therefore this similarity has been utilized to develop an accurate, adaptive algorithm for the detection of red lesions, wherein every fundus image is processed with a different intensity threshold value resulting more accurate detection.
机译:本文提出了一种算法,用于检测眼睛眼底上存在的红色病变。红色病变包括微动脉瘤和出血,这是糖尿病视网膜病变的症状,一种普遍的眼部疾病,这在患者生活中几乎影响了几乎每一个糖尿病患者。本文呈现了一种检测图像中存在的红色病变的自适应方法。基于本地图像信息,所提出的方法将估计给定的眼底图像的红色病变的上阈值和较低阈值。这种算法的自适应性质的重要性是从不同相机获取的眼底图像可能质量和分辨率变化。结果,红色病变的强度可以从图像变化到图像。由于,红色病变的强度类似于特定图像的血管的强度,因此已经利用这种相似性来开发用于检测红色病变的准确,自适应算法,其中每个眼底图像都以不同的强度处理阈值导致更准确的检测。

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