Name
Title | ||
|---|---|---|
Deep Attention and Graphical Neural Network for Multiple Sclerosis Lesion Segmentation From MR Imaging Sequences |
Abstract | ||
|---|---|---|
The segmentation of multiple sclerosis (MS) lesions from MR imaging sequences remains a challenging task, due to the characteristics of variant shapes, scattered distributions and unknown numbers of lesions. However, the current automated MS segmentation methods with deep learning models face the challenges of (1) capturing the scattered lesions in multiple regions and (2) delineating the global c... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/JBHI.2021.3109119 | IEEE Journal of Biomedical and Health Informatics |
Keywords | DocType | Volume |
Lesions,Correlation,Image segmentation,Multiple sclerosis,Feature extraction,Convolution,Bioinformatics | Journal | 26 |
Issue | ISSN | Citations |
3 | 2168-2194 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhanlan Chen | 1 | 0 | 0.34 |
| Xiuying Wang | 2 | 161 | 33.25 |
| Jing Huang | 3 | 0 | 0.68 |
| Jie Lu | 4 | 51 | 6.19 |
| Jiang-bin Zheng | 5 | 104 | 18.02 |