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Combining YAWL and DBNs for Surgical Phase Detection : Technical Report IES-2016-01

Philipp, Patrick

Abstract:
To provide assistance functions in context of surgical interventions,
the use of a surgical phase detection plays an important role. By
assessing the progress of an on-going surgery, a tailored (i.e., context sensitive)
decision support for medical practitioners can be enabled. Subsequently,
this provides opportunities to prevent errors, injuries, negligence
or malpractices. In this work, a surgical phase detection, combining Yet
Another Workflow Language (YAWL) with Dynamic Bayesian Networks
(DBNs) is proposed. Thereby, YAWL is used to model the relationship
of surgical phases; DBNs are used to allow for the detection of surgical
phases of interest. The approach is presented for the application example of
a cholecystectomy (removal of the gallbladder).


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Jahr 2017
Sprache Englisch
Identifikator ISBN: 978-3-7315-0678-2
ISSN: 1863-6489
URN: urn:nbn:de:swb:90-723440
KITopen ID: 1000072344
Erschienen in Proceedings of the 2016 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision an Fusion Laboratory. Ed.: J. Beyerer
Verlag KIT Scientific Publishing, Karlsruhe
Seiten 1-15
Serie Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe ; 33
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