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Issue No. 01 - January/February (2009 vol. 24)
ISSN: 1541-1672
pp: 57-65
Daniel L. Rubin , Stanford University
Pattanasak Mongkolwat , Northwestern University
Vladimir Kleper , Northwestern University
Kaustubh Supekar , Stanford University
David S. Channin , Northwestern University
Medical images are proliferating at an explosive pace, similar to other types of data in e-Science. While Semantic Web techniques are being created to access much raw biomedical data, the rich information in images is not currently accessible. We are creating methods and tools to enable people to access large distributed collections of medical images in cyberspace as well as within hospital information systems. In this report, we describe our approach, "Annotation and Image Markup" (AIM), in which human and machine descriptions of image content is made explicit and accessible using ontologies. AIM includes the following components: an ontology of image annotation and markup, specifying entities and relations to represent the semantics of images; an image annotation tool to collect annotations from people viewing images as instances of the ontology; and a serialization module to store the image annotation information in a variety of standard formats, enabling interoperability among a variety of systems that contain images: medical records systems, image archives in hospitals, and the Semantic Web. Through these methods, we hope to enable the scientific community who work with images to access their semantic contents and integrate them with related non-imaging information so they exploit the image information effectively.
intelligent web services, semantic web, ontology design, image representation

P. Mongkolwat, V. Kleper, D. S. Channin, K. Supekar and D. L. Rubin, "Annotation and Image Markup: Accessing and Interoperating with the Semantic Content in Medical Imaging," in IEEE Intelligent Systems, vol. 24, no. , pp. 57-65, 2009.
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