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

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

Diabetic retinopathy (DR) is an eye abnormality caused by chronic diabetes that affected patients worldwide. Hard exudate is an important and observable sign of DR and can be used for early diagnosis. In this paper, an automatic hard exudates segmentation method is proposed in order to aid ophthalmo...

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Bibliographic Details
Main Authors: Yongshuo Zong, Jinling Chen, Lvqing Yang, Siyi Tao, Cieryouzhen Aoma, Jiangsheng Zhao, Shuihua Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep learning
diabetic retinopathy
exudates segmentation
superpixel
U-net
Online Access:https://ieeexplore.ieee.org/document/9194249/

Internet

https://ieeexplore.ieee.org/document/9194249/

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