Name
Abstract | ||
|---|---|---|
•A novel convolutional neural network is proposed, which can generate high-resolution feature maps to preserve spatial details.•The spatial and channel-wise attention mechanisms are adopted to enhance representative features while suppressing noise.•The proposed network can accurately extract skin lesion boundaries, and is robust to hair fibers and artifacts in the images. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.cmpb.2019.105241 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Skin lesion segmentation,Convolutional neural network,High-resolution feature,Attention mechanism | Spatial analysis,Computer vision,Lesion,Computer science,Medical imaging,Segmentation,Convolutional neural network,Feature extraction,Jaccard index,Artificial intelligence,Discriminative model | Journal |
Volume | ISSN | Citations |
186 | 0169-2607 | 2 |
PageRank | References | Authors |
0.37 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fengying Xie | 1 | 182 | 15.33 |
| Jiawen Yang | 2 | 2 | 0.37 |
| Jie Liu | 3 | 105 | 43.72 |
| Zhiguo Jiang | 4 | 321 | 45.58 |
| Yushan Zheng | 5 | 2 | 0.70 |
| Yukun Wang | 6 | 2 | 0.37 |