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|Abstract=In the surgical domain, individual clinical experience plays an important role in the treatment decision process. Keeping an overview of the large amount of diverse information available about the individual patient, ranging from anamnesis to diagnostic data as well as imaging and intraoperative sensors, while keeping up-to-date with the growing knowledge derived from clinical studies poses a big challenge to the surgeon. Our interdisciplinary and multi-institutional approach aims to create a cognitive surgical assistance system which utilizes these extensive clinical data sets as well as derived individual data like enhanced three-dimensional geometric descriptions of organs or biomechanical simulations in order to create individual treatment recommendations. A fundamental requirement of such a system is a flexible data storage that provides standardized access to users and applications.
 
|Abstract=In the surgical domain, individual clinical experience plays an important role in the treatment decision process. Keeping an overview of the large amount of diverse information available about the individual patient, ranging from anamnesis to diagnostic data as well as imaging and intraoperative sensors, while keeping up-to-date with the growing knowledge derived from clinical studies poses a big challenge to the surgeon. Our interdisciplinary and multi-institutional approach aims to create a cognitive surgical assistance system which utilizes these extensive clinical data sets as well as derived individual data like enhanced three-dimensional geometric descriptions of organs or biomechanical simulations in order to create individual treatment recommendations. A fundamental requirement of such a system is a flexible data storage that provides standardized access to users and applications.
 
In this work we present a semantic data infrastructure that is capable of integrating these very heterogeneous data sources on the basis of a common knowledge representation. A combination of the XNAT imaging informatics platform with semantic web technologies and custom interfaces enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual treatment recommendations. Suc- cessful use cases from various projects show the applicability of the approach and of the system which is built completely using free technologies and will be made available to the community as an open source package.
 
In this work we present a semantic data infrastructure that is capable of integrating these very heterogeneous data sources on the basis of a common knowledge representation. A combination of the XNAT imaging informatics platform with semantic web technologies and custom interfaces enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual treatment recommendations. Suc- cessful use cases from various projects show the applicability of the approach and of the system which is built completely using free technologies and will be made available to the community as an open source package.
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|Download=Sfb-infrastructure-spie2016.pdf,
 
|Projekt=SFB/Transregio 125
 
|Projekt=SFB/Transregio 125
 
|Forschungsgruppe=Web Science und Wissensmanagement
 
|Forschungsgruppe=Web Science und Wissensmanagement
 
}}
 
}}

Version vom 19. Februar 2016, 13:36 Uhr


Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery


Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery



Published: 2016 März

Buchtitel: SPIE Medical Imaging Proceedings
Verlag: SPIE Digital Library
Erscheinungsort: San Diego, CA, United States

Referierte Veröffentlichung

BibTeX

Kurzfassung
In the surgical domain, individual clinical experience plays an important role in the treatment decision process. Keeping an overview of the large amount of diverse information available about the individual patient, ranging from anamnesis to diagnostic data as well as imaging and intraoperative sensors, while keeping up-to-date with the growing knowledge derived from clinical studies poses a big challenge to the surgeon. Our interdisciplinary and multi-institutional approach aims to create a cognitive surgical assistance system which utilizes these extensive clinical data sets as well as derived individual data like enhanced three-dimensional geometric descriptions of organs or biomechanical simulations in order to create individual treatment recommendations. A fundamental requirement of such a system is a flexible data storage that provides standardized access to users and applications. In this work we present a semantic data infrastructure that is capable of integrating these very heterogeneous data sources on the basis of a common knowledge representation. A combination of the XNAT imaging informatics platform with semantic web technologies and custom interfaces enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual treatment recommendations. Suc- cessful use cases from various projects show the applicability of the approach and of the system which is built completely using free technologies and will be made available to the community as an open source package.

Download: Media:Sfb-infrastructure-spie2016.pdf

Projekt

SFB/Transregio 125



Forschungsgruppe

Web Science und Wissensmanagement


Forschungsgebiet