Name
Abstract | ||
|---|---|---|
•A graph neural network (GNN) can learn global vascular structures in medical images.•A CNN only learns local appearances on the regular image grid and thus can be limited.•The vessel graph network (VGN) combines a GNN into a comprehensive CNN architecture.•The VGN jointly learns both local appearance and global structure of vessels.•The VGN structure can be applied to any existing CNN structure to improve accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.media.2019.101556 | Medical Image Analysis |
Keywords | Field | DocType |
Vessel segmentation,Convolutional neural network,Graph neural network,Vessel graph network | Vessel segmentation,Graph,Pattern recognition,Computer science,Segmentation,Retinal image,Artificial intelligence,Grid | Journal |
Volume | ISSN | Citations |
58 | 1361-8415 | 8 |
PageRank | References | Authors |
0.46 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seung Yeon Shin | 1 | 20 | 1.72 |
| Soochahn Lee | 2 | 52 | 9.16 |
| Il Dong Yun | 3 | 344 | 36.57 |
| Kyoung Mu Lee | 4 | 3228 | 153.84 |