Name
Title | ||
|---|---|---|
Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair. |
Abstract | ||
|---|---|---|
The proposed method is fully automatic, fast and segments aortic stent grafts in fluoroscopic images with high accuracy. The quality and performance of the segmentation will allow for an intraoperative comparison with the preoperative information to assess the accuracy of the fusion. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11548-018-1779-6 | Int. J. Computer Assisted Radiology and Surgery |
Keywords | Field | DocType |
Aortic stents,EVAR,Fluoroscopy,Convolutional neural network,Deep learning,Segmentation | Stent,Segmentation,Fluoroscopy,Radiation exposure,Radiology,Medicine,Aorta | Journal |
Volume | Issue | ISSN |
13 | 8 | 1861-6410 |
Citations | PageRank | References |
3 | 0.37 | 15 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Katharina Breininger | 1 | 3 | 1.05 |
| Shadi Albarqouni | 2 | 169 | 22.17 |
| Tanja Kurzendorfer | 3 | 14 | 7.38 |
| Marcus Pfister | 4 | 89 | 9.75 |
| Markus Kowarschik | 5 | 222 | 42.67 |
| Andreas K. Maier | 6 | 560 | 178.76 |