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Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery

Du, X; Allan, M; Dore, A; Ourselin, S; Hawkes, D; Kelly, JD; Stoyanov, D; (2016) Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery. International Journal of Computer Assisted Radiology and Surgery , 11 (6) pp. 1109-1119. 10.1007/s11548-016-1393-4. Green open access

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Abstract

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.

Type: Article
Title: Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11548-016-1393-4
Publisher version: http://dx.doi.org/10.1007/s11548-016-1393-4
Language: English
Additional information: Copyright © The Author(s) 2016. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Instrument tracking and detection, Minimally invasive surgery, Robot-assisted surgery, Surgical vision
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1480794
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