title: Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy.
abstract: OBJECTIVE
  Computer assistance is increasingly common in surgery. However, the amount of information is bound to overload processing abilities of surgeons. We propose methods to recognize the current phase of a surgery for context-aware information filtering. The purpose is to select the most suitable subset of information for surgical situations which require special assistance.
  
  
  METHODS
  We combine formal knowledge, represented by an ontology, and experience-based knowledge, represented by training samples, to recognize phases. For this purpose, we have developed two different methods. Firstly, we use formal knowledge about possible phase transitions to create a composition of random forests. Secondly, we propose a method based on cultural optimization to infer formal rules from experience to recognize phases.
  
  
  RESULTS
  The proposed methods are compared with a purely formal knowledge-based approach using rules and a purely experience-based one using regular random forests. The comparative evaluation on laparoscopic pancreas resections and adrenalectomies employs a consistent set of quality criteria on clean and noisy input. The rule-based approaches proved best with noisefree data. The random forest-based ones were more robust in the presence of noise.
  
  
  CONCLUSIONS
  Formal and experience-based knowledge can be successfully combined for robust phase recognition.
authors.affiliation: Institute for Anthropomatics and Robotics (IAR), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany. katic@kit.edu.
authors.forename: Darko
authors.initials: D
authors.lastname: Katić
authors.affiliation: Institute for Anthropomatics and Robotics (IAR), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Schuck
authors.affiliation: Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
authors.forename: Anna-Laura
authors.initials: AL
authors.lastname: Wekerle
authors.affiliation: Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
authors.forename: Hannes
authors.initials: H
authors.lastname: Kenngott
authors.affiliation: Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
authors.forename: Beat Peter
authors.initials: BP
authors.lastname: Müller-Stich
authors.affiliation: Institute for Anthropomatics and Robotics (IAR), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Dillmann
authors.affiliation: Institute for Anthropomatics and Robotics (IAR), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Speidel
mesh_terms: D000465:Algorithms; D003663:Decision Trees; D006801:Humans; D051188:Knowledge Bases; D010535:Laparoscopy / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*
keywords: Cognition-guided assistance; Context-awareness; Ontology