Exudate Detection with Improved U-Net Using Fundus Images-Reference-Cited by-同舟云学术

Exudate Detection with Improved U-Net Using Fundus Images

Published:2021-12-01 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Computational Performance Evaluation (ComPE)
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Author:

Mohan N Jagan¹,Murugan R¹,Goel Tripti¹,Roy Parthapratim²

Affiliation:

1. National Institute of Technology, Silchar,Bio-Medical Imaging Laboratory (BIOMIL),Dept. of ECE,Silchar,Assam,India

2. Silchar Medical College and Hospital,Department of Ophthalmology,Silchar,Assam,India

Funder

Science and Engineering Research Board

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9751776/9751720/09752239.pdf?arnumber=9752239

Reference24 articles.

1. Detection of hard exudates in retinal fundus images using deep learning;benzamin;2018 Joint 7th International Conference on Informatics Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging Vision & Pattern Recognition (icIVPR),2018

2. Exudate segmentation using fully convolutional neural networks and inception modules

3. An Enhanced Residual U-Net for Microaneurysms and Exudates Segmentation in Fundus Images

4. Modified U-Net architecture for semantic segmentation of diabetic retinopathy images

5. U-net Based Method for Automatic Hard Exudates Segmentation in Fundus Images Using Inception Module and Residual Connection

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