Surgical tool attributes from monocular video

Suren Kumar, Madusudanan Sathia Narayanan, Pankaj Singhal, Jason J. Corso, Venkat Krovi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

HD Video from the (monocular or binocular) endoscopic camera provides a rich real-time sensing channel from surgical site to the surgeon console in various Minimally Invasive Surgery (MIS) procedures. However, a real-time framework for video understanding would be critical for tapping into the rich information-content provided by the non-invasive and well-established digital endoscopic video-streaming modality. While contemporary research focuses on enhancing aspects such as tool-tracking within the challenging visual scenes, we consider the associated problem of using that rich (but often compromised) streaming visual data to discover the underlying semantic attributes of the tools. Directly analyzing the surgical videos to extract more realistic attributes online can aid in the decision-making and feedback aspects. We propose a novel probabilistic attribute labelling framework with Bayesian filtering to identify associated semantics (open/closed, stained with blood etc.) to ultimately give semantic feedback to the surgeon. Our robust video-understanding framework overcomes many of the challenges (tissue deformations, image specularities, clutter, tool-occlusion due to blood and/or organs) under realistic in-vivo surgical conditions. Specifically, this manuscript performs rigorous experimental analysis of the resulting method with varying parameters and different visual features on a data-corpus consisting of real surgical procedures performed on patients with da Vinci Surgical System [9].

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Pages4887-4892
Number of pages6
ISBN (Electronic)9781479936854, 9781479936854
DOIs
StatePublished - 22 Sep 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: 31 May 20147 Jun 2014

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2014 IEEE International Conference on Robotics and Automation, ICRA 2014
Country/TerritoryChina
CityHong Kong
Period31/05/147/06/14

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