Name
Title | ||
|---|---|---|
Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization. |
Abstract | ||
|---|---|---|
•A joint learning framework for both bone segmentation and landmark digitization.•A displacement map is used to explicitly model the spatial context information.•Results achieved by our method are clinically acceptable.•Only 1 min to complete both tasks of bone segmentation and landmark digitization. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.media.2019.101621 | Medical Image Analysis |
Keywords | Field | DocType |
Cone-beam computed tomography,Landmark digitization,Bone segmentation,Fully convolutional networks | Voxel,Computer vision,Digitization,Pattern recognition,Segmentation,Displacement mapping,Artificial intelligence,Computed tomography,Bone segmentation,Spatial contextual awareness,Landmark,Mathematics | Journal |
Volume | ISSN | Citations |
60 | 1361-8415 | 1 |
PageRank | References | Authors |
0.36 | 0 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Zhang | 1 | 342 | 27.73 |
| Mingxia Liu | 2 | 432 | 41.14 |
| Li Wang | 3 | 1051 | 78.25 |
| Si Chen | 4 | 44 | 26.77 |
| Peng Yuan | 5 | 24 | 7.54 |
| Jianfu Li | 6 | 13 | 3.75 |
| Steve G F Shen | 7 | 15 | 3.06 |
| Zhen Tang | 8 | 18 | 3.44 |
| Ken Chung Chen | 9 | 15 | 3.04 |
| James J. Xia | 10 | 64 | 16.52 |
| Dinggang Shen | 11 | 7837 | 611.27 |