eprintid: 10119196
rev_number: 18
eprint_status: archive
userid: 608
dir: disk0/10/11/91/96
datestamp: 2021-01-22 16:17:22
lastmod: 2022-02-16 18:16:34
status_changed: 2021-01-22 16:17:22
type: article
metadata_visibility: show
creators_name: Robu, M
creators_name: Kadkhodamohammadi, A
creators_name: Luengo, I
creators_name: Stoyanov, D
title: Towards real-time multiple surgical tool tracking
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Multiple tool tracking, Surgical data science, Computer-Assisted Interventions
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
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.
date: 2021
date_type: published
official_url: https://doi.org/10.1080/21681163.2020.1835553
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1838339
doi: 10.1080/21681163.2020.1835553
lyricists_name: Stoyanov, Danail
lyricists_id: DSTOY26
actors_name: Stoyanov, Danail
actors_id: DSTOY26
actors_role: owner
full_text_status: public
publication: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
volume: 9
number: 3
pagerange: 279-285
citation:        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 <https://doi.org/10.1080/21681163.2020.1835553>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10119196/1/2020CMBBE_Robu.pdf