Workflow analysis and surgical phase recognition in minimally invasive surgery

Oliver Weede, Frank Dittrich, Heinz Worn, Brian Jensen, Alois Knoll, Dirk Wilhelm, Michael Kranzfelder, Armin Schneider, Hubertus Feussner

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

26 Scopus citations

Abstract

In this paper, a new approach is described to recognize the phases of a single-port sigma resection intraoperatively, based on the position signal of the surgical instruments, the endoscopic video and an audio signal, signaling coagulations. Approaches for detecting the coagulation sounds, as well as the instruments visible in the endoscopic video using a bag of words model are detailed. The intervention phases are regarded as classes of a naive Bayes classifier. Features that differentiate intervention phases are examined. The naive Bayes classifier is extended by a dynamic feature, which includes the order of the intervention phases and their duration. First results show that in 93.2% the recognized phases are classified as true positive.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest
Pages1068-1074
Number of pages7
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Guangzhou, China
Duration: 11 Dec 201214 Dec 2012

Publication series

Name2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest

Conference

Conference2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012
Country/TerritoryChina
CityGuangzhou
Period11/12/1214/12/12

Keywords

  • Cognitive medical technology
  • high-level task recognition
  • object recognition
  • sound recognition
  • trajectory segmentation
  • workflow analysis

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