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Proceedings Paper

Ontology-based prediction of surgical events in laparoscopic surgery
Author(s): Darko Katić; Anna-Laura Wekerle; Fabian Gärtner; Hannes Kenngott; Beat Peter Müller-Stich; Rüdiger Dillmann; Stefanie Speidel
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Paper Abstract

Context-aware technologies have great potential to help surgeons during laparoscopic interventions. Their underlying idea is to create systems which can adapt their assistance functions automatically to the situation in the OR, thus relieving surgeons from the burden of managing computer assisted surgery devices manually. To this purpose, a certain kind of understanding of the current situation in the OR is essential. Beyond that, anticipatory knowledge of incoming events is beneficial, e.g. for early warnings of imminent risk situations. To achieve the goal of predicting surgical events based on previously observed ones, we developed a language to describe surgeries and surgical events using Description Logics and integrated it with methods from computational linguistics. Using n-Grams to compute probabilities of followup events, we are able to make sensible predictions of upcoming events in real-time. The system was evaluated on professionally recorded and labeled surgeries and showed an average prediction rate of 80%.

Paper Details

Date Published: 15 March 2013
PDF: 7 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86711A (15 March 2013); doi: 10.1117/12.2007895
Show Author Affiliations
Darko Katić, Karlsruher Institut für Technologie (Germany)
Anna-Laura Wekerle, Heidelberg Univ. (Germany)
Fabian Gärtner, Karlsruher Institut für Technologie (Germany)
Hannes Kenngott, Heidelberg Univ. (Germany)
Beat Peter Müller-Stich, Heidelberg Univ. (Germany)
Rüdiger Dillmann, Karlsruher Institut für Technologie (Germany)
Stefanie Speidel, Karlsruher Institut für Technologie (Germany)

Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes III; Ziv R. Yaniv, Editor(s)

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