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.


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    Titel :

    Towards real-time multiple surgical tool tracking


    Beteiligte:
    Robu, M (Autor:in) / Kadkhodamohammadi, A (Autor:in) / Luengo, I (Autor:in) / Stoyanov, D (Autor:in)

    Erscheinungsdatum :

    2021-01-01


    Anmerkungen:

    Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization , 9 (3) pp. 279-285. (2021)


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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