基于形状的眼底图像提取技术自动检测糖尿病视网膜病变红色病灶

Aman Pandey, Ritu Chandra, M. Dutta, Radim Burget, V. Uher, Jiri Minar
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引用次数: 5

摘要

提出了一种基于形状特征的图像自动处理算法,用于红色病灶的检测。在糖尿病视网膜病变中,微动脉瘤和出血属于红色病变的范畴,是糖尿病患者最常见的眼病,也会导致失明。本文描述了一种有效的方法来研究任何计算机辅助眼底图像,可以用作诊断和检测红色病变的工具。一种基于形状的提取技术,使用三个参数,即周长面积和偏心率,从图像的其余部分分割出红色病灶。由于该算法考虑了红色病灶的形状特征,使得其检测效率高,且不受图像质量的影响。应用该算法得到的实验结果与眼科医生的结果进行了比较,比较结果具有较高的准确性。该方法不仅计算精度高,而且速度快,计算时间短。
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Automatic detection of red lesions in Diabetic Retinopathy using Shape based extraction technique in fundus image
The paper proposes an automatic image processing algorithm based on shape features for the detection of red lesions. In Diabetic Retinopathy Micro-aneurysms and hemorrhages comes under the category of red lesions, which is the most common eye disease caused in diabetic patients and also leads to blindness. This paper describes an effective methodology to study any computer-aided fundus image that can be utilized as a tool for diagnosis and detection of red lesions. A Shape based extraction technique using three parameters i.e. Perimeter Area and Eccentricity is used to segment out the red lesions from rest of the image. Since the algorithm consider shape features for detection of red lesion which makes it efficient and independent of image quality. The results that are experimentally obtained by applying this algorithm has been compared with those of the ophthalmologist and the comparison of these results have been highly accurate. In addition to the accuracy of the obtained results, the proposed method is fast and having very low computational time.
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