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Convolutional network to detect exudates in eye fundus images of diabetic subjects

机译:卷积网络可检测糖尿病受试者眼底图像中的渗出液

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Diabetic retinopathy has several clinical data sources for medical diagnosis, but the lack of tools to process the data generates a subjective and unclear diagnosis. The use of convolutional networks to analyze and extract features in eye fundus images may help with an automatic detection to support medical personnel in the grading of diabetic retinopathy. This paper presents a description of convolutional neural networks as a good methodology to detect and discriminate between exudate and healthy regions in eye fundus images.
机译:糖尿病性视网膜病有几种用于医学诊断的临床数据来源,但是缺乏处理数据的工具会产生主观且不清楚的诊断。使用卷积网络分析和提取眼底图像中的特征可能有助于自动检测,以支持医务人员进行糖尿病性视网膜病变的分级。本文介绍了卷积神经网络,作为检测和区分眼底图像中渗出液和健康区域的良好方法。

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