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Identification and Classification of Retinal Lesions for Early Detection of Diabetic Retinopathy using Fundal Image

机译:眼底图像识别和分类以早期发现糖尿病性视网膜病变

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Diabetic Retinopathy (DR) is a human eye disease which may cause damage to retina of eye, it may lead to complete blindness. Currently diabetic retinopathy is detected using different types of lesions such as Microaneursyms (MAs), Exudates (EXs) and Hemorrhages (HAs). This paper focuses on the identification and classification of lesions for early detection of Diabetic retinopathy through hybrid morphological approach. In the proposed approach the detection of DR is performed through hybrid pre-post processing methods to enhance the lesion detection execution. In addition by using the area of boundaries scheme, the affected regions are identified as initial, middle and severe stage. Performance analysis of the proposed method is demonstrated using Matlab software. Simulation studies on available database prove that the hybrid approach has improved performance over classical approach.
机译:糖尿病性视网膜病(DR)是一种人眼疾病,可能会损害眼睛的视网膜,并可能导致完全失明。当前,糖尿病视网膜病变使用不同类型的病变如微动脉瘤(MA),渗出液(EX)和出血(HA)来检测。本文着重于通过混合形态学方法对糖尿病视网膜病变的病灶进行识别和分类。在所提出的方法中,通过混合的前后处理方法来执行DR的检测,以增强病变检测的执行。此外,通过使用边界面积方案,可以将受影响区域识别为初期,中期和严重阶段。使用Matlab软件演示了该方法的性能分析。对可用数据库的仿真研究证明,混合方法比传统方法具有更高的性能。

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