An Ontology to Support Adaptive Training for Breast Radiologists

Authors:
Shanghua Sun;Paul Taylor;Louise Wilkinson;Lisanne Khoo
Affiliations:
Centre for Health Informatics and Multiprofessional Education, University College London, UK;Centre for Health Informatics and Multiprofessional Education, University College London, UK;Duchess of Kent Breast Screening Unit, St George's NHS Trust, London, UK;Duchess of Kent Breast Screening Unit, St George's NHS Trust, London, UK
Venue:
IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
Year:
2008

Citing 4
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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.