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118646

Deep Learning Grading System for Diabetic Retinopathy using Fundus Images.

Article

Last updated: 04 Jan 2025

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Tags

Electrical Engineering

Abstract

Diabetic Retinopathy (DR) is one of the main causes of blindness that can be overcome, if it is early detected. This work proposes an automated early detection and grading of DR using fundus images. The proposed detection and grading system investigate different deep learning architectures (i.e., ResNet and AlexNet) that are applied to an augment data to extract deep compact features of the fundus images. The extracted features are input to a pixel-wise Neural Network (NN) classifier or a Support Vector Machine (SVM) classifier for automated DR grading. The performance of the proposed system is evaluated using a publically available fundus Indian Diabetic Retinopathy Image Dataset (IDRiD), collected for ISBI-2018 challenge. The IDRiD dataset consists of 516 retinal images of normal and different DR grades, i.e., mild, moderate, severe, and Proliferative Diabetic Retinopathy (PDR). Our system achieves an overall accuracy of 95.73%, sensitivity of 95.73%, and specificity of 98.51% utilizing an AlexNet-based architecture and a pixel-wise NN classifier. Compared to the previous related work, the proposed system shows promising DR grading performance.

DOI

10.21608/bfemu.2020.118646

Keywords

Deep learning, fundus images, diabetic retinopathy, Grading

Authors

First Name

Doaa

Last Name

Elsawah

MiddleName

-

Affiliation

ECE department, Faculty of Engineering, Mansoura University, Egypt

Email

doaakhalil313@gmail.com

City

Masnoura

Orcid

-

First Name

Ahmed

Last Name

Elnakib

MiddleName

-

Affiliation

ECE department, Faculty of Engineering, Mansoura University, Egypt

Email

nakib@mans.edu.eg

City

Masnoura

Orcid

0000-0001-6084-3622

First Name

Hossam El-Din

Last Name

Moustafa

MiddleName

Salah

Affiliation

Faculty of Engineering, Mansoura University, Mansoura, Egypt

Email

hossam_moustafa@hotmail.com

City

-

Orcid

-

Volume

45

Article Issue

4

Related Issue

17795

Issue Date

2020-12-01

Receive Date

2020-07-12

Publish Date

2020-10-14

Page Start

1

Page End

8

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 45_Issue 4_Pages 1-8.pdf

PDF . 818.6kB

Link

https://bfemu.journals.ekb.eg/article_118646.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=118646

Order

19

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

Deep Learning Grading System for Diabetic Retinopathy using Fundus Images.

Details

Type

Article

Created At

22 Jan 2023