Publikation: Surgical Action Retrieval for Assisting...
Stammdaten
Titel: | Surgical Action Retrieval for Assisting Video Review of Laparoscopic Skills |
Untertitel: | |
Kurzfassung: | An increasing number of surgeons promote video review of laparoscopic surgeries for detection of technical errors at an early stage as well as for training purposes. The reason behind is the fact that laparoscopic surgeries require specific psychomotor skills, which are difficult to learn and teach. The manual inspection of surgery video recordings is extremely cumbersome and time-consuming. Hence, there is a strong demand for automated video content analysis methods. In this work, we focus on retrieving surgical actions from video collections of gynecologic surgeries. We propose two novel dynamic content descriptors for similarity search and investigate a query-by-example approach to evaluate the descriptors on a manually annotated dataset consisting of 18 hours of video content. We compare several content descriptors including dynamic information of the segments as well as descriptors containing only spatial information of keyframes of the segments. The evaluation shows that our proposed dynamic content descriptors considering motion and spatial information from the segment achieve a better retrieval performance than static content descriptors ignoring temporal information of the segment at all. The proposed content descriptors in this work enable content-based video search for similar laparoscopic actions, which can be used to assist surgeons in evaluating laparoscopic surgical skills. |
Schlagworte: |
Publikationstyp: | Beitrag in Sammelwerk (Autorenschaft) |
Erscheinungsdatum: | 10.2017 (Online) |
Erschienen in: |
MultiEdTech '17 Proceedings of the 2017 ACM Workshop on Multimedia-based Educational and Knowledge Technologies for Personalized and Social Online Training
MultiEdTech '17 Proceedings of the 2017 ACM Workshop on Multimedia-based Educational and Knowledge Technologies for Personalized and Social Online Training
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ACM Digital Library;
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zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 11 - 19 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 10.2017 |
ISBN (e-book): |
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eISSN: | - |
DOI: | http://dx.doi.org/10.1145/3132390.3132395 |
Homepage: | https://dl.acm.org/citation.cfm?id=3132395 |
Open Access |
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AutorInnen
Sabrina Kletz (intern) | ||||
Klaus Schöffmann (intern) | ||||
Bernd Münzer (intern) | ||||
Manfred Jürgen Primus (intern) | ||||
Heinrich Husslein
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Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
Kategorisierung
Sachgebiete | |
Forschungscluster | Kein Forschungscluster ausgewählt |
Peer Reviewed |
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Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
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Arbeitsgruppen |
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Kooperationen
Organisation | Adresse | ||
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Medizinische Universität Wien
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AT - 1090 Wien |
Forschungsaktivitäten
(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
Projekte: | Keine verknüpften Projekte vorhanden |
Publikationen: | Keine verknüpften Publikationen vorhanden |
Veranstaltungen: | Keine verknüpften Veranstaltung vorhanden |
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