Robu, M;
Kadkhodamohammadi, A;
Luengo, I;
Stoyanov, D;
(2021)
Towards real-time multiple surgical tool tracking.
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
, 9
(3)
pp. 279-285.
10.1080/21681163.2020.1835553.
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Abstract
Surgical tool tracking is an essential building block for computer-assisted interventions (CAI) and applications like video summarisation, workflow analysis and surgical navigation. Vision-based instrument tracking in laparoscopic surgical data faces significant challenges such as fast instrument motion, multiple simultaneous instruments and re-initialisation due to out-of-view conditions or instrument occlusions. In this paper, we propose a real-time multiple object tracking framework for whole laparoscopic tools, which extends an existing single object tracker. We introduce a geometric object descriptor, which helps with overlapping bounding box disambiguation, fast motion and optimal assignment between existing trajectories and new hypotheses. We achieve 99.51% and 75.64% average accuracy on ex-vivo robotic data and in-vivo laparoscopic sequences respectively from the Endovis’15 Instrument Tracking Dataset. The proposed geometric descriptor increased the performance on laparoscopic data by 32%, significantly reducing identity switches, false negatives and false positives. Overall, the proposed pipeline can successfully recover trajectories over long-sequences and it runs in real-time at approximately 25–29 fps.
| Type: | Article |
|---|---|
| Title: | Towards real-time multiple surgical tool tracking |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/21681163.2020.1835553 |
| Publisher version: | https://doi.org/10.1080/21681163.2020.1835553 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Multiple tool tracking, Surgical data science, Computer-Assisted Interventions |
| UCL classification: | UCL 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 |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10119196 |
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