Anomaly Detection System for Retinal Images Based on Area Classifier

M. A. Amer, M. Rihan, S. El-Agooz, Noha A. El-Hag, W. El-shafai, F. El-Samie, A. Khalaf, Ghada M. El-Banby, M. Abdelhamed
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Abstract

Diabetic Retinopathy (DR) is a disease of the eye for diabetics, and it can lead to a lack of vision if leaved untreated. The proposed approach in this paper is used to help for detecting and classifying the DR. It is applied to detect non-proliferative DR by identifying micro-aneurysms and hemorrhages. Firstly, the pre-processing step is applied. It consists of extracting the green channel, removing the optic disc (OD) and normalizing the background. Then, h-maxima transformation is performed. After that, threshold segmentation is applied to detect the hemorrhages and micro-aneurysms, accurately. Finally, an area classifier is used for the classification process to discriminate dark spot lesions.
基于区域分类器的视网膜图像异常检测系统
糖尿病视网膜病变(DR)是糖尿病患者的一种眼部疾病,如果不及时治疗,可能会导致视力下降。本文提出的方法用于帮助DR的检测和分类,它通过识别微动脉瘤和出血来检测非增殖性DR。首先,应用预处理步骤。它包括提取绿色通道、去除视盘(OD)和归一化背景。然后,进行h-maxima变换。然后,应用阈值分割,准确检测出出血和微动脉瘤。最后,利用区域分类器对黑斑病变进行分类。
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