Deep Learning Techniques for Diabetic Retinopathy Detection

Author(s): Sehrish Qummar, Fiaz Gul Khan*, Sajid Shah, Ahmad Khan, Ahmad Din, Jinfeng Gao

Journal Name: Current Medical Imaging
Formerly: Current Medical Imaging Reviews

Volume 16 , Issue 10 , 2020

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Abstract:

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.

Keywords: Diabetic retinopathy, deep learning, convolutional Neural Network, diabetes, machine learning, lesions detection.

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Article Details

VOLUME: 16
ISSUE: 10
Year: 2020
Page: [1201 - 1213]
Pages: 13
DOI: 10.2174/1573405616666200213114026
Price: $65

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