Name
Abstract | ||
|---|---|---|
Accurate segmentation of anatomical structures is vital for medical image analysis. The state-of-the-art accuracy is typically achieved by supervised learning methods, where gathering the requisite expert-labeled image annotations in a scalable manner remains a main obstacle. Therefore, annotation-efficient methods that permit to produce accurate anatomical structure segmentation are highly desira... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TMI.2020.3043375 | IEEE Transactions on Medical Imaging |
Keywords | DocType | Volume |
Image segmentation,Shape,Training,Biomedical imaging,Anatomical structure,X-ray imaging,Task analysis | Journal | 40 |
Issue | ISSN | Citations |
10 | 0278-0062 | 0 |
PageRank | References | Authors |
0.34 | 0 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhang Lu | 1 | 17 | 4.62 |
| Kang Zheng | 2 | 42 | 7.41 |
| Weijian Li | 3 | 24 | 6.42 |
| Yirui Wang | 4 | 4 | 1.06 |
| Adam P. Harrison | 5 | 101 | 17.06 |
| Chi-Hung Lin | 6 | 217 | 34.67 |
| Song Wang | 7 | 954 | 79.55 |
| Jing Xiao | 8 | 7 | 5.78 |
| Le Lu | 9 | 1297 | 86.78 |
| Chang-Fu Kuo | 10 | 0 | 1.35 |
| Shun Miao | 11 | 143 | 17.54 |