Name
Title | ||
|---|---|---|
Unsupervised Domain Adaptation Based Image Synthesis and Feature Alignment for Joint Optic Disc and Cup Segmentation |
Abstract | ||
|---|---|---|
Due to the discrepancy of different devices for fundus image collection, a well-trained neural network is usually unsuitable for another new dataset. To solve this problem, the unsupervised domain adaptation strategy attracts a lot of attentions. In this paper, we propose an unsupervised domain adaptation method based image synthesis and feature alignment (ISFA) method to segment optic disc and cu... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/JBHI.2021.3085770 | IEEE Journal of Biomedical and Health Informatics |
Keywords | DocType | Volume |
Image segmentation,Feature extraction,Image synthesis,Training,Optical imaging,Image edge detection,Generators | Journal | 26 |
Issue | ISSN | Citations |
1 | 2168-2194 | 1 |
PageRank | References | Authors |
0.35 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haijun Lei | 1 | 1 | 0.35 |
| Weixin Liu | 2 | 1 | 0.35 |
| Hai Xie | 3 | 9 | 5.30 |
| Benjian Zhao | 4 | 1 | 0.35 |
| Guanghui Yue | 5 | 86 | 16.46 |
| Bai Ying Lei | 6 | 119 | 24.99 |