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Proceedings Paper

Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery
Author(s): Andreas Fetzer; Jasmin Metzger; Darko Katic; Keno März; Martin Wagner; Patrick Philipp; Sandy Engelhardt; Tobias Weller; Sascha Zelzer; Alfred Michael Franz; Nicolai Schoch; Vincent Heuveline; Maria Maleshkova; Achim Rettinger; Stefanie Speidel; Ivo Wolf; Hannes Kenngott; Arianeb Mehrabi; Beat P. Müller-Stich; Lena Maier-Hein; Hans-Peter Meinzer; Marco Nolden
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Paper Abstract

In the surgical domain, individual clinical experience, which is derived in large part from past clinical cases, plays an important role in the treatment decision process. Simultaneously the surgeon has to keep track of a large amount of clinical data, emerging from a number of heterogeneous systems during all phases of surgical treatment. This is complemented with the constantly growing knowledge derived from clinical studies and literature. To recall this vast amount of information at the right moment poses a growing challenge that should be supported by adequate technology. While many tools and projects aim at sharing or integrating data from various sources or even provide knowledge-based decision support - to our knowledge - no concept has been proposed that addresses the entire surgical pathway by accessing the entire information in order to provide context-aware cognitive assistance. Therefore a semantic representation and central storage of data and knowledge is a fundamental requirement. We present a semantic data infrastructure for integrating heterogeneous surgical data sources based on a common knowledge representation. A combination of the Extensible Neuroimaging Archive Toolkit (XNAT) with semantic web technologies, standardized interfaces and a common application platform enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual context-aware surgical assistance. The infrastructure meets the requirements of a cognitive surgical assistant system and has been successfully applied in various use cases. The system is based completely on free technologies and is available to the community as an open-source package.

Paper Details

Date Published: 25 March 2016
PDF: 8 pages
Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890O (25 March 2016); doi: 10.1117/12.2217163
Show Author Affiliations
Andreas Fetzer, German Cancer Research Ctr. (Germany)
Jasmin Metzger, German Cancer Research Ctr. (Germany)
Darko Katic, Karlsruhe Institute of Technology (Germany)
Keno März, German Cancer Research Ctr. (Germany)
Martin Wagner, Heidelberg Univ. Hospital (Germany)
Patrick Philipp, Karlsruhe Institute of Technology (Germany)
Sandy Engelhardt, German Cancer Research Ctr. (Germany)
Tobias Weller, Karlsruhe Institute of Technology (Germany)
Sascha Zelzer, German Cancer Research Ctr. (Germany)
Alfred Michael Franz, German Cancer Research Ctr. (Germany)
Nicolai Schoch, Heidelberg Univ. (Germany)
Vincent Heuveline, Heidelberg Univ. (Germany)
Maria Maleshkova, Karlsruhe Institute of Technology (Germany)
Achim Rettinger, Karlsruhe Institute of Technology (Germany)
Stefanie Speidel, Karlsruhe Institute of Technology (Germany)
Ivo Wolf, Mannheim Univ. of Applied Sciences (Germany)
Hannes Kenngott, Heidelberg Univ. Hospital (Germany)
Arianeb Mehrabi, Heidelberg Univ. Hospital (Germany)
Beat P. Müller-Stich, Heidelberg Univ. Hospital (Germany)
Lena Maier-Hein, German Cancer Research Ctr. (Germany)
Hans-Peter Meinzer, German Cancer Research Ctr. (Germany)
Marco Nolden, German Cancer Research Ctr. (Germany)


Published in SPIE Proceedings Vol. 9789:
Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations
Jianguo Zhang; Tessa S. Cook, Editor(s)

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