Abstract
Medical education and training increasingly rely on computer-based tools. A number of initiatives incorporate digital libraries in tools to train radiologists. Our research involves the use of an informatics infrastructure to access a database of annotated images. We argue that an intelligent training tool requires a rich annotation of images in the database. In order to allow for the flexible querying of the database and intelligent feedback to trainees, those annotations must be organised using a clear and explicit model of the relevant concepts: an ontology. The paper reviews existing work on ontologies for mammography and outlines a new approach which is (a) derived from a detailed analysis of a large number of cases and (b) rich enough to meet the requirements of a training tool.
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Sun, S., Taylor, P., Wilkinson, L., Khoo, L. (2008). An Ontology to Support Adaptive Training for Breast Radiologists. In: Krupinski, E.A. (eds) Digital Mammography. IWDM 2008. Lecture Notes in Computer Science, vol 5116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70538-3_36
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DOI: https://doi.org/10.1007/978-3-540-70538-3_36
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