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Binary endoscope localization from laparoscopic video as virtual sensor for automatic workflow detection

  • This paper contributes to the automatic detection of perioperative workflow by developing a binary endoscope localization. Automated situation recognition in the context of an intelligent operating room requires the automatic conversion of low level cues into more abstract high level information. Imagery from a laparoscope delivers rich content that is easy to obtain but hard to process. We introduce a system which detects if the endoscope's distal tip is inside or outsiede the patient based on the endoscope video. This information can be used as one parameter in a situation recognition pipeline. Our localization performs in real-time at a video resolution of 1280x720 and 5-fold cross validation yields mean F1-scores of up to 0,94 on videos of 7 laparoscopies.

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Metadaten
Name:Scheytt, Josia; Wiemuth, Markus; Burgert, Oliver
ISBN:978-3-95900-158-8
Erschienen in:CURAC 2017 - Tagungsband : 16. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) : 5.-7. Oktober 2017, Hannover
Publisher:PZH Verlag, TEWISS-Technik und Wissen GmbH
Place of publication:Garbsen
Editor:Jessica Burgner-Kahrs
Document Type:Conference Proceeding
Language:English
Year of Publication:2017
Tag:endoscope localization; laparoscopic surgery; situation recognition
Pagenumber:6
First Page:191
Last Page:196
Catalogue entry:Im Katalog der Hochschule Reutlingen ansehen
Dewey Decimal Classification:610 Medizin, Gesundheit
Open Access:Nein