Name
Title | ||
|---|---|---|
Inconsistency-Aware Uncertainty Estimation for Semi-Supervised Medical Image Segmentation |
Abstract | ||
|---|---|---|
In semi-supervised medical image segmentation, most previous works draw on the common assumption that higher entropy means higher uncertainty. In this paper, we investigate a novel method of estimating uncertainty. We observe that, when assigned different misclassification costs in a certain degree, if the segmentation result of a pixel becomes inconsistent, this pixel shows a relative uncertainty... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TMI.2021.3117888 | IEEE Transactions on Medical Imaging |
Keywords | DocType | Volume |
Uncertainty,Image segmentation,Estimation,Training,Biomedical imaging,Computational modeling,Task analysis | Journal | 41 |
Issue | ISSN | Citations |
3 | 0278-0062 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yinghuan Shi | 1 | 200 | 28.94 |
| Jian Zhang | 2 | 0 | 1.01 |
| Tong Ling | 3 | 0 | 0.34 |
| Jiwen Lu | 4 | 3105 | 153.88 |
| Yefeng Zheng | 5 | 1391 | 114.67 |
| Qian Yu | 6 | 272 | 23.02 |
| Lei Qi | 7 | 27 | 8.76 |
| Yang Gao | 8 | 528 | 50.36 |