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.
| Author of HS Reutlingen | Scheytt, Josia; Wiemuth, Markus; Burgert, Oliver |
|---|---|
| URL: | https://www.curac.org/images/advportfoliopro/images/CURAC2017/2017_CURAC_Tagungsband_Compiled_V1.7_final.pdf |
| 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: | Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e. V. |
| Place of publication: | Stuttgart |
| Editor: | Jessica Burgner-Kahrs |
| Document Type: | Conference proceeding |
| Language: | English |
| Publication year: | 2017 |
| Tag: | endoscope localization; laparoscopic surgery; situation recognition |
| Page Number: | 6 |
| First Page: | 191 |
| Last Page: | 196 |
| PPN: | Im Katalog der Hochschule Reutlingen ansehen |
| DDC classes: | 610 Medizin, Gesundheit |
| Open access?: | Ja |
| Licence (German): |  Open Access |
