Name
Abstract | ||
|---|---|---|
•We for the first time investigate the novel-view projection synthesis problem for X-ray imaging. The approach can also be generalized to a more general synthesis from multi-views to multi-views projections.•We propose a deep learning-based geometry-integrated projection synthesis model (DL-GIPS) to generate novel-view X-ray projections through feature disentanglement and geometry transformation.•We validate the feasibility of the proposed approach by experimenting on the one-to-one and multi-to-multi X-ray projection synthesis using lung imaging cases across various patients. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.media.2022.102372 | Medical Image Analysis |
Keywords | DocType | Volume |
Projection view synthesis,X-ray imaging,Geometry-integrated deep learning | Journal | 77 |
Issue | ISSN | Citations |
3 | 1361-8415 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liyue Shen | 1 | 13 | 1.56 |
| Lequan Yu | 2 | 706 | 39.80 |
| Wei Zhao | 3 | 3532 | 404.01 |
| John M. Pauly | 4 | 600 | 52.05 |
| Lei Xing | 5 | 102 | 23.72 |