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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Veröffentlicht in:	IEEE access 2020, Vol.8, p.167225-167235
Hauptverfasser:	Zong, Yongshuo, Chen, Jinling, Yang, Lvqing, Tao, Siyi, Aoma, Cieryouzhen, Zhao, Jiangsheng, Wang, Shuihua
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biomedical imaging Classification algorithms Computer architecture Datasets Deep learning Diabetes Diabetic retinopathy Diagnosis exudates segmentation Exudation Feature extraction Image color analysis Image segmentation Machine learning Modules superpixel U-net
Online-Zugang:	Volltext
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