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.

Preview

Text 2020CMBBE_Robu.pdf - Accepted Version Download (3MB) | Preview

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.

Download activity - last month

Export as JSONCSVXML

Download activity - last 12 months

Export as XMLCSVJSON

Downloads by country - last 12 months

Export as XMLCSVJSON

Archive Staff Only

View Item