Name
Title | ||
|---|---|---|
DA-DSUnet: Dual Attention-based Dense SU-net for automatic head-and-neck tumor segmentation in MRI images |
Abstract | ||
|---|---|---|
•Unpooling is adopted to get over boundary ambiguity.•Convolutional blocks are replaced by dense blocks to for parameters reduction.•A dual attention mechanism is proposed for feature refinement.•A composite loss function is introduced to alleviate vanishing-gradient problem.•The proposed method can be applied to nasopharyngeal carcinoma segmentation in clinic. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.neucom.2020.12.085 | Neurocomputing |
Keywords | DocType | Volume |
Nasopharyngeal carcinoma,Image segmentation,Attention mechanism,DA-DSUnet,Magnetic resonance images | Journal | 435 |
ISSN | Citations | PageRank |
0925-2312 | 1 | 0.36 |
References | Authors | |
0 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pin Tang | 1 | 1 | 0.70 |
| Chen Zu | 2 | 25 | 4.99 |
| Mei Hong | 3 | 1 | 1.71 |
| Rui Yan | 4 | 1 | 0.36 |
| Xingchen Peng | 5 | 1 | 0.70 |
| Jianghong Xiao | 6 | 1 | 0.36 |
| Xi Wu | 7 | 7 | 1.18 |
| Jiliu Zhou | 8 | 450 | 58.21 |
| Luping Zhou | 9 | 498 | 43.89 |
| Yan Wang | 10 | 168 | 28.11 |