Applications of an Ontology Engineering Methodology Accessing Linked Data for Medical Image Retrieval

Daniel Sonntag, Pinar Wennerberg, Sonja Zillner

In: Proceedings of the AAAI Spring Symposium "Linked Data meets Artificial Intelligence". AAAI Spring Symposium (AAAI SSS) March 22-24 Stanford CA United States Stanford University 2010.


This paper examines first ideas on the applicability of Linked Data, in particular a subset of the Linked Open Drug Data (LODD), to connect radiology, human anatomy, and drug information for improved medical image annotation and subsequent search. One outcome of our ontology engineering methodology is the alignment between radiology-related OWL ontologies (FMA and RadLex). These can be used to provide new connections in the medicine-related linked data cloud. A use case scenario is provided that demonstrates the benefits of the approach by enabling the radiologist to query and explore related data, e.g., medical images and drugs. The diagnosis is on a special type of cancer (lymphoma).


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2010_Applications_of_an_Ontology_Engineering_Methodology_Accessing_Linked_Data_for_Medical_Image_Retrieval_.pdf (pdf, 239 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence