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Computer aided diagnostic system for grading of diabetic retinopathy

机译:糖尿病视网膜病变分级计算机辅助诊断系统

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The automated detection and diagnosis of Diabetic Retinopathy (DR) is very critical to save the patient's vision and to help the ophthalmologists in mass screening of diabetes sufferers. DR is a progressive eye disease and should be detected as early as possible. In this paper, we present a new system for detection and classification of different DR lesions i.e. Microaneurysms (MAs), Haemorrhage (H), Hard Exudates (HE) and Cotton Wool Spots (CWS). We proposed a three stage system in which first stage extracts all possible candidate lesions present in a fundus image suing filter bank. Then feature sets are computed for each candidate lesion using different properties and features followed by classification of lesions. The evaluation of proposed system is performed using retinal image databases with the help of different performance matrices and the results show the validity of proposed system.
机译:糖尿病视网膜病变(DR)的自动检测和诊断对于挽救患者的视力并帮助眼科医生对糖尿病患者进行大规模筛查至关重要。 DR是一种进行性眼部疾病,应尽早发现。在本文中,我们介绍了一种用于检测和分类不同DR病变的新系统,即微动脉瘤(MAs),出血(H),硬性渗出液(HE)和棉绒斑点(CWS)。我们提出了一个三阶段系统,其中第一阶段通过过滤器库提取眼底图像中存在的所有可能的候选病变。然后,使用不同的属性和特征为每个候选病变计算特征集,然后对病变进行分类。在不同性能矩阵的帮助下,利用视网膜图像数据库对提出的系统进行了评估,结果表明了提出系统的有效性。

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