Name
Abstract | ||
|---|---|---|
Intraoperative tracking of laparoscopic instruments is a prerequisite to realize further assistance functions. Since endoscopic images are always available, this sensor input can be used to localize the instruments without special devices or robot kinematics. In this paper, we present an image-based markerless 3D tracking of different da Vinci instruments in near real-time without an explicit model. The method is based on different visual cues to segment the instrument tip, calculates a tip point and uses a multiple object particle filter for tracking. The accuracy and robustness is evaluated with in vivo data. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1117/12.2042483 | Proceedings of SPIE |
Keywords | Field | DocType |
Endoscopic Vision,Localization & Tracking Technologies,Endoscopic Image Processing,Robotic-assisted surgery | Sensory cue,Computer vision,Laparoscopic surgery,Kinematics,Particle filter,Robot kinematics,Robustness (computer science),Eye tracking,Artificial intelligence,Robotic assisted surgery,Physics | Conference |
Volume | ISSN | Citations |
9036 | 0277-786X | 5 |
PageRank | References | Authors |
0.48 | 5 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefanie Speidel | 1 | 313 | 39.70 |
| e kuhn | 2 | 5 | 0.48 |
| Sebastian Bodenstedt | 3 | 91 | 16.46 |
| s rohl | 4 | 9 | 1.91 |
| Hannes Kenngott | 5 | 104 | 22.28 |
| Beat P. Müller-Stich | 6 | 79 | 12.09 |
| Rüdiger Dillmann | 7 | 433 | 43.19 |