Estimating similarity of surgical situations with Case-Retrieval-Nets
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Representation and recognition of surgical situations is a prerequisite for the development of context-aware surgical assistance systems. In this publication a method for recognition of surgical situations with Case-Retrieval-Nets is presented. It enables the estimation of similarity between models of surgical situations. The main advantage of this approach is the combined use of domain knowledge and reasoning algorithms to estimate similarity. Domain knowledge about human anatomy is based on a reference ontology. Evaluation is performed on situations of two cholecystectomies.
Details
Originalsprache | Englisch |
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Titel | Medicine Meets Virtual Reality 17 - NextMed |
Herausgeber (Verlag) | IOS Press |
Seiten | 358-363 |
Seitenumfang | 6 |
ISBN (Print) | 9781586039646 |
Publikationsstatus | Veröffentlicht - 2009 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | Studies in health technology and informatics |
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Band | 142 |
ISSN | 0926-9630 |
Konferenz
Titel | 17th Annual MMVR Conference - NextMed: Design for/the Well Being, MMVR17 2009 |
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Dauer | 19 - 22 Januar 2009 |
Stadt | Long Beach, CA |
Land | USA/Vereinigte Staaten |
Externe IDs
PubMed | 19377184 |
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ORCID | /0000-0002-4590-1908/work/163294165 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Case-based-reasoning, Situation recognition, Surgical situation