Name
Title | ||
|---|---|---|
Fusion of intraoperative force sensoring, surface reconstruction and biomechanical modeling |
Abstract | ||
|---|---|---|
Minimally invasive surgery is medically complex and can heavily benefit from computer assistance. One way to help the surgeon is to integrate preoperative planning data into the surgical workflow. This information can be represented as a customized preoperative model of the surgical site. To use it intraoperatively, it has to be updated during the intervention due to the constantly changing environment. Hence, intraoperative sensor data has to be acquired and registered with the preoperative model. Haptic information which could complement the visual sensor data is still not established. In addition, biomechanical modeling of the surgical site can help in reflecting the changes which cannot be captured by intraoperative sensors. We present a setting where a force sensor is integrated into a laparoscopic instrument. In a test scenario using a silicone liver phantom, we register the measured forces with a reconstructed surface model from stereo endoscopic images and a finite element model. The endoscope, the instrument and the liver phantom are tracked with a Polaris optical tracking system. By fusing this information, we can transfer the deformation onto the finite element model. The purpose of this setting is to demonstrate the principles needed and the methods developed for intraoperative sensor data fusion. One emphasis lies on the calibration of the force sensor with the instrument and first experiments with soft tissue. We also present our solution and first results concerning the integration of the force sensor as well as accuracy to the fusion of force measurements, surface reconstruction and biomechanical modeling. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1117/12.911406 | Proceedings of SPIE |
Keywords | Field | DocType |
Image-Guided Therapy,Force sensoring,Sensor data fusion,Registration,Finite Element modelling | Computer vision,Surface reconstruction,Imaging phantom,Finite element method,Sensor fusion,Scenario testing,Artificial intelligence,Image-Guided Therapy,Haptic technology,Calibration,Physics | Conference |
Volume | ISSN | Citations |
8316 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| s rohl | 1 | 9 | 1.91 |
| Sebastian Bodenstedt | 2 | 91 | 16.46 |
| c kuderle | 3 | 0 | 0.34 |
| Stefan Suwelack | 4 | 41 | 5.89 |
| Hannes Kenngott | 5 | 104 | 22.28 |
| Beat P. Müller-Stich | 6 | 79 | 12.09 |
| Rüdiger Dillmann | 7 | 2201 | 262.95 |
| Stefanie Speidel | 8 | 313 | 39.70 |