D. Lavanya, D. Derwin, R. Remya, B. Shan, O. Singh, Umamaheswari. K
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引用次数: 1
Abstract
Diabetic Retinopathy (DR) is a chronic disease that may cause vision loss in diabetic patients. A regular eye screening is essential to grade the stages of DR such as Microaneurysms (MAs), exudates and drusen in retinal images acquired using fundus camera. Microaneurysm is an early stage of DR, characterized by small red spots on the retina due to blood and fluid leakage from the weak capillary wall. Hence early detection is vital in preventing the diabetic retinopathy and this article explores an automatic screening system that focus on the early detection of DR which is referred as Microaneurysm. The proposed automatic decision system follow the stages of acquisition of color fundus images, pre-processing the input fundus image, manual selection of Microaneurysm area by Region Of Interest (ROI) and classification of diabetic retinopathy is more helpful for early detection and analysis of diabetic retinopathy. The detection process comprises of image pre-processing, feature extraction and classification methods. The proposed method has been applied to color fundus image in feature extraction, classification and provided with improved outcomes for detecting Microaneurysm.
糖尿病视网膜病变(DR)是一种可导致糖尿病患者视力丧失的慢性疾病。定期的眼部筛查对于DR的分期至关重要,如眼底相机拍摄的视网膜图像中的微动脉瘤(MAs)、渗出物和水肿。微动脉瘤是DR的早期阶段,其特征是由于血液和液体从薄弱的毛细血管壁渗漏而导致视网膜上的小红点。因此,早期发现对于预防糖尿病视网膜病变至关重要,本文探讨了一种专注于早期发现DR的自动筛查系统,即微动脉瘤。本文提出的自动决策系统经过彩色眼底图像的采集、输入眼底图像的预处理、根据感兴趣区域(Region of Interest, ROI)手动选择微动脉瘤区域以及糖尿病视网膜病变的分类等步骤,更有助于糖尿病视网膜病变的早期发现和分析。检测过程包括图像预处理、特征提取和分类方法。该方法已应用于彩色眼底图像的特征提取和分类,为微动脉瘤的检测提供了较好的结果。