Name
Abstract | ||
|---|---|---|
•We propose the Scale Attention mechanism, which is effective for multi-scale problem in liver tumor segmentation.•We improve the self-attention and propose the Axis Attention mechanism, which is efficient and effective for spatial information modeling globally.•We combine the Scale Attention and the Axis Attention mechanisms organically with a style of adaptive global pooling in SAA-Net, which is efficient for preserving fine-grained information in global pooling, beneficial to final segmentation. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.bspc.2021.103460 | Biomedical Signal Processing and Control |
Keywords | DocType | Volume |
Liver tumor segmentation,U-shaped,Scale Attention,Axis Attention | Journal | 73 |
ISSN | Citations | PageRank |
1746-8094 | 1 | 0.36 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chi Zhang | 1 | 1 | 0.36 |
| Jingben Lu | 2 | 1 | 0.36 |
| Qianqian Hua | 3 | 1 | 0.36 |
| Chunguo Li | 4 | 48 | 10.72 |
| Pengwei Wang | 5 | 1 | 0.36 |