首页> 外文会议>Proceedings of 2016 IEEE International Conference on Control and Robotics Engineering >Autogenous diabetic retinopathy censor for ophthalmologists ??? AKSHI
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Autogenous diabetic retinopathy censor for ophthalmologists ??? AKSHI

机译:眼科医生的自体糖尿病性视网膜病变检查仪阿克西

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The Diabetic Retinopathy (DR) is a rapidly growing interrogation around the world which can be annotated by abortive metabolism of glucose that causes long-term infection in human retina. This is one of the preliminary reason of visual impairment and blindness of adults. Information on retinal pathological mutation can be recognized using ocular fundus images. In this research, we are mainly focused on resurrecting an automated diagnosis system to detect DR anomalies such as severity level classification of DR patient (Non-proliferative Diabetic Retinopathy approach) and vessel tortuosity measurement of untwisted vessels to assessment of vessel anomalies (Proliferative Diabetic Retinopathy approach). Severity classification method is obtained better results according to the precision, recall, F-measure and accuracy (exceeds 94%) in all formats of cross validation. In ROC (Receiver Operating Characteristic) curves also visualized the higher AUC (Area Under Curve) percentage (exceeds 95%). User level evaluation of severity capturing is obtained higher accuracy (85%) result and fairly better values for each evaluation measurements. Untwisted vessel detection for tortuosity measurement also carried out the good results with respect to the sensitivity (85%), specificity (89%) and accuracy (87%).
机译:糖尿病性视网膜病(DR)是世界范围内正在迅速发展的一种审讯,其现象可以通过葡萄糖的流产性新陈代谢来注释,葡萄糖会导致人类视网膜的长期感染。这是成年人视力障碍和失明的主要原因之一。可以使用眼底图像识别有关视网膜病理突变的信息。在这项研究中,我们主要致力于恢复自动诊断系统以检测DR异常,例如DR患者的严重程度分级(非增生性糖尿病性视网膜病变方法)和未扭曲血管的血管曲折度测量以评估血管异常(增生性糖尿病性视网膜病变)方法)。在所有交叉验证格式中,严重性分类方法均根据精度,召回率,F度量和准确性(超过94%)获得更好的结果。在ROC(接收机工作特性)曲线中,可视化的AUC(曲线下面积)百分比也更高(超过95%)。用户级别的严重性捕获评估获得了更高的准确性(85%)结果,并且每次评估测量的值都相当好。用于扭曲度测量的无扭曲血管检测在灵敏度(85%),特异性(89%)和准确性(87%)方面也取得了良好的结果。

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