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A Deep Learning Method for the detection of Diabetic Retinopathy

机译:一种检测糖尿病性视网膜病变的深度学习方法

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Many Diabetic patients suffer from a medical condition in the retina of the eye known as Diabetic Retinopathy. The main cause of Diabetic Retinopathy is high blood sugar levels over a long period of time in the retina known as Diabetes Mellitus. The primary goal is to automatically classify patients having diabetic retinopathy and not having the same, given any High-Resolution Fundus Image of the Retina. For that an initial image processing has been done on the images which includes mainly, conversion of coloured (RGB) images into perfect greyscale and resizing it. Then, a Deep Learning Approach is applied in which the processed image is fed into a Convolutional Neural Network to predict whether the patient is diabetic or not. This methodology is applied on a dataset of 30 High Resolution Fundus Images of the retina. The results, so obtained are a 100 % predictive accuracy and a Sensitivity of 100 % also. Such an Automated System can easily classify images of the retina among Diabetic and Healthy patients, reducing the number of reviews of doctors.
机译:许多糖尿病患者患有被称为糖尿病性视网膜病的眼内疾病。糖尿病性视网膜病的主要原因是在很长一段时间内视网膜中的高血糖水平,被称为糖尿病。给定任何高分辨率的视网膜眼底图像,主要目的是自动对患有糖尿病性视网膜病且没有糖尿病性视网膜病的患者进行分类。为此,已经对图像进行了初始图像处理,主要包括将彩色(RGB)图像转换为完美的灰度并调整其大小。然后,应用深度学习方法,其中将处理后的图像输入到卷积神经网络中,以预测患者是否患有糖尿病。该方法应用于30个视网膜高分辨率眼底图像的数据集。如此获得的结果是100%的预测精度和100%的灵敏度。这样的自动化系统可以轻松地对糖尿病和健康患者的视网膜图像进行分类,从而减少了医生的诊治次数。

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