Abstract

The web has become such an extensive health information repository in the world that it is increasingly difficult to search for relevant medical information. Most medical information available on the web is not peer reviewed, and is retrieved imprecisely by current web search mechanisms (i.e. based on keywords). This paper presents the MedISeek metadata model that allows one to describe medical visual information (i.e. medical images) of different modalities, including their properties, components, relationships and authorship. The model uses the web architecture and supports the international classification of diseases and related health problems (i.e. ICD-10). An RDF schema (Resource Description Framework (RDF), http://www.w3.org/RDF/.) derived from this metadata model is integrated to each medical image, and specifies the semantics of each property in the image. Thus, relevant information can be extracted directly from the images, and data integrity is better preserved in the web. A prototype, presented here, has been built to validate the metadata model, and the mechanism for medical visual information exchange on the web. Our preliminary experimental results indicate that authorized users of our system have been able to describe, store and retrieve medical images and their associated diagnostic information.