Video Summarization of Laparoscopic Cholecystectomies

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dc.contributor.authorGrasso, Michael A.
dc.contributor.authorFinin, Tim
dc.contributor.authorZhu, Xianshu
dc.contributor.authorJoshi, Anupam
dc.contributor.authorYesha, Yelena
dc.date.accessioned2018-11-16T15:20:47Z
dc.date.available2018-11-16T15:20:47Z
dc.date.issued2009-11-14
dc.descriptionProceedings of the AMIA 2009 Annual Symposium; San Francisco, CA; November 14, 2009 - November 18, 2009en
dc.description.abstractWe compared image features with a distance metric and support vector machine to identify the critical view of a laparoscopic cholecystectomy. Our accuracy was up to 91%. We are currently experimenting with particle analysis, edge analysis, and feature clus-tering to create a more robust image classifier.en
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/453/Video-Summarization-of-Laparoscopic-Cholecystectomiesen
dc.format.extent1 pageen
dc.genrepreprints
dc.genreconference papers and proceedingsen
dc.identifierdoi:10.13016/M28S4JT0Z
dc.identifier.urihttp://hdl.handle.net/11603/12023
dc.language.isoenen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectVideo Summarizationen
dc.subjectCholecystectomiesen
dc.subjectLaparoscopicen
dc.subjectUMBC Ebiquity Research Groupen
dc.titleVideo Summarization of Laparoscopic Cholecystectomiesen
dc.typeTexten
dcterms.creatorhttps://orcid.org/0000-0001-6455-6508
dcterms.creatorhttps://orcid.org/0000-0002-6593-1792
dcterms.creatorhttps://orcid.org/0000-0002-8641-3193

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