Name
Abstract | ||
|---|---|---|
•A novel correlation description block is introduced to discover the latent multi-source correlation between modalities.•A constraint based on the correlation using KL divergence is proposed to aide the segmentation network to extract the correlated feature representation for a better segmentation.•A tri-attention fusion strategy is proposed to recalibrate the feature representation along modality-attention, spatial-attention and correlation-attention paths.•The first 3D multi-modal brain tumor segmentation network guided by tri-attention fusion is proposed. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.patcog.2021.108417 | Pattern Recognition |
Keywords | DocType | Volume |
Multi-modality fusion,Correlation,Brain tumor segmentation,Deep learning | Journal | 124 |
ISSN | Citations | PageRank |
0031-3203 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tongxue Zhou | 1 | 22 | 2.94 |
| Ruan Su | 2 | 559 | 53.00 |
| Pierre Vera | 3 | 59 | 10.15 |
| Stéphane Canu | 4 | 827 | 82.61 |