An Efficient AI Based System for the Detection of Diabetic Maculopathy Using Colour Fundus Images-Reference-Cited by-同舟云学术

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An Efficient AI Based System for the Detection of Diabetic Maculopathy Using Colour Fundus Images

Published:2024-07-04 Issue: Volume: Page:1-8
ISSN:
Container-title:2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)
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Author:

Bhoopalan Ramasubramanian¹,S Priyadharshini.²,Anbalagan Sriram¹,Mathu Venkateswaran³,Sabpathy Sundersan.⁴

Affiliation:

1. SRMTRP Engineering College,Dept. of ECE,Tiruchirappalli,Tamilnadu,India

2. SRM TRPEngineering College,Tiruchirappalli,Tamilnadu,India

3. Lendi Institute of Engineering and Technology,Dept.of EEE,Vizianagaram,India

4. School of AI,Department of Computational Engineering and Networking, Amrita Viswa Vidyapeetham,Coimbatore,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10625767/10627770/10627839.pdf?arnumber=10627839

Reference22 articles.

1. CANet: Cross-Disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading

2. Diabetic Retinopathy Detection Using Prognosis of Microaneurysm and Early Diagnosis System for Non-Proliferative Diabetic Retinopathy Based on Deep Learning Algorithms

3. Vision Transformer Model for Predicting the Severity of Diabetic Retinopathy in Fundus Photography-Based Retina Images

4. Automated diagnosis of referable maculopathy in diabetic retinopathy screening

5. Segmentation in Diabetic Retinopathy using Deeply-Supervised Multiscalar Attention

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