PURPOSE: Computer-assisted interventions for enhanced minimally invasive surgery (MIS) require tracking of the surgical instruments. Instrument tracking is a challenging problem in both conventional and robotic-assisted MIS, but vision-based approaches are a promising solution with minimal hardware integration requirements. However, vision-based methods suffer from drift, and in the case of occlusions, shadows and fast motion, they can be subject to complete tracking failure. METHODS: In this paper, we develop a 2D tracker based on a Generalized Hough Transform using SIFT features which can both handle complex environmental changes and recover from tracking failure. We use this to initialize a 3D tracker at each frame which enables us to recover 3D instrument pose over long sequences and even during occlusions. RESULTS: We quantitatively validate our method in 2D and 3D with ex vivo data collected from a DVRK controller as well as providing qualitative validation on robotic-assisted in vivo data. CONCLUSIONS: We demonstrate from our extended sequences that our method provides drift-free robust and accurate tracking. Our occlusion-based sequences additionally demonstrate that our method can recover from occlusion-based failure. In both cases, we show an improvement over using 3D tracking alone suggesting that combining 2D and 3D tracking is a promising solution to challenges in surgical instrument tracking.
Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery
2016-06-01
International Journal of Computer Assisted Radiology and Surgery , 11 (6) pp. 1109-1119. (2016)
Article (Journal)
Electronic Resource
English
DDC: | 629 |
3D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery
BASE | 2018
|Robot-Assisted Minimally Invasive Surgery-Surgical Robotics in the Data Age
BASE | 2022
|Hand-eye calibration for robotic assisted minimally invasive surgery without a calibration object
BASE | 2016
|Online Contents | 1994