Pillars of Ontology Treatment in the Medical Domain

Daniel Sonntag (DFKI - German Research Center for Artificial Intelligence, Germany), Pinar Wennerberg (Externer Dienstleister der Siemens AG, Germany), Paul Buitelaar (DERI - National University of Ireland, Galway, Ireland), and Sonja Zillner (Siemens AG, Germany)
Copyright: © 2010 |Pages: 186
EISBN13: 9781616921866|DOI: 10.4018/978-1-60566-894-9.ch008
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Abstract

In this chapter the authors describe the three pillars of ontology treatment in the medical domain in a comprehensive case study within the large-scale THESEUS MEDICO project. MEDICO addresses the need for advanced semantic technologies in medical image and patient data search. The objective is to enable a seamless integration of medical images and different user applications by providing direct access to image semantics. Semantic image retrieval should provide the basis for the help in clinical decision support and computer aided diagnosis. During the course of lymphoma diagnosis and continual treatment, image data is produced several times using different image modalities. After semantic annotation, the images need to be integrated with medical (textual) data repositories and ontologies. They build upon the three pillars of knowledge engineering, ontology mediation and alignment, and ontology population and learning to achieve the objectives of the MEDICO project.
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