Deep Learning Techniques for Diabetic Retinopathy Detection

被引:3
作者
Qummar, Sehrish [1 ,2 ]
Khan, Fiaz Gul [1 ]
Shah, Sajid [1 ]
Khan, Ahmad [1 ]
Din, Ahmad [1 ]
Gao, Jinfeng [2 ]
机构
[1] COMSATS Univ Islamabad, Dept Comp Sci, Abbottabad Campus, Abbottabad, Pakistan
[2] Huanghuai Univ, Dept Informat Engn, Zhumadian, Henan, Peoples R China
关键词
Diabetic retinopathy; deep learning; convolutional Neural Network; diabetes; machine learning; lesions detection; AUTOMATED DETECTION; NEURAL-NETWORK; IMAGES; ALGORITHMS; DIAGNOSIS; LESIONS; AREA;
D O I
10.2174/1573405616666200213114026
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Diabetes occurs due to the excess of glucose in the blood that may affect many organs of the body. Elevated blood sugar in the body causes many problems including Diabetic Retinopathy (DR). DR occurs due to the mutilation of the blood vessels in the retina. The manual detection of DR by ophthalmologists is complicated and time-consuming. Therefore, automatic detection is required, and recently different machine and deep learning techniques have been applied to detect and classify DR. In this paper, we conducted a study of the various techniques available in the literature for the identification/classification of DR, the strengths and weaknesses of available datasets for each method, and provides the future directions. Moreover, we also discussed the different steps of detection, that are: segmentation of blood vessels in a retina, detection of lesions, and other abnormalities of DR.
引用
收藏
页码:1201 / 1213
页数:13
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