Name
Abstract | ||
|---|---|---|
Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis. Retraining models leads to high latency and complex pipelines, which are impractical in clinical settings. The situation becomes more severe for ultrasound image analysis because of their large appearance shifts. In this paper, we propose a novel method for robust segment... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISBI48211.2021.9433930 | 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) |
Keywords | DocType | ISSN |
Image segmentation,Analytical models,Ultrasonic imaging,Image analysis,Biological system modeling,Pipelines,Robustness | Conference | 1945-7928 |
ISBN | Citations | PageRank |
978-1-6654-1246-9 | 0 | 0.34 |
References | Authors | |
0 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhendong Liu | 1 | 0 | 0.34 |
| Xiaoqiong Huang | 2 | 4 | 2.51 |
| Xin Yang | 3 | 79 | 9.59 |
| Rui Gao | 4 | 0 | 0.34 |
| Rui Li | 5 | 0 | 1.35 |
| Yuanji Zhang | 6 | 0 | 1.69 |
| Yankai Huang | 7 | 0 | 0.34 |
| Guangquan Zhou | 8 | 15 | 4.63 |
| Yi Xiong | 9 | 0 | 2.37 |
| Alejandro F. Frangi | 10 | 0 | 0.34 |
| Dong Ni | 11 | 367 | 37.37 |