A Deep Learning Approach to Diabetic Retinopathy Classification

被引:1
|
作者
Oishi, Anika Mehjabin [1 ]
Tawfiq-Uz-Zaman, Md [1 ]
Emon, Mohammad Billal Hossain [1 ]
Momen, Sifat [1 ]
机构
[1] North South Univ, Dept Elect & Comp Engn, Dhaka 1229, Bangladesh
关键词
Classification; Convolutional neural network; Diabetic retinopathy; Retinal fundus images;
D O I
10.1007/978-3-031-09073-8_36
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Diabetic retinopathy is a serious ophthalmic disorder, caused by the damaging of retina due to high blood sugar. Depending on the severity of the problem, diabetic retinopathy can be categorized into one of the four classes (i.e. mild, moderate, severe and proliferate). In this work, we have applied Convolutional Neural Network on the retinal fundus images to classify the images into one of the five classes (no diabetic retinopathy, along with the four different classes). Different convolutional neural network architectures were used to correctly classify retinal fundus images into its category. Empirical results indicate that we can classify diabetic retinopathy from the fundus images reliably.
引用
收藏
页码:417 / 425
页数:9
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