A New Concept for Classification of Medical Images
Part of the Informatik aktuell book series (INFORMAT)


Content-based image retrieval (CBIR) provides novel options to access large repositories of medical images. Thus, there are new opportunities for storing, querying and reporting especially within the field of digital radiology. This, however, requires a revisit of nomenclatures for image classification. The Digital Imaging and Communication in Medicine (DICOM), for instance, defines only about 20, partly overlapping terms for coding the body region. In 2002, the Image Retrieval in Medical Applications (IRMA) project has proposed a mono-hierarchic, multi-axial coding scheme. Although the initial concept of the IRMA Code was designed for later expansion, the appliance of the terminology in the practice of scientific projects discovered several weak points. In this paper, based on a systematic analysis and the comparison with other relevant medical ontologies such as the Lexicon for Uniform Indexing and Retrieval of Radiology Information Resources (RadLex), we accordingly propose axes for medical equipment, findings and body positioning as well as additional flags for age, body part, ethnicity, gender, image quality and scanned film. The IRMA Code II may be used in the Cross Language Evaluation Campaign (CLEF) annotation tasks as a database of classified images to evaluate visual information retrieval systems.


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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Medical InformaticsRWTH Aachen UniversityAachenDeutschland
  2. 2.Medical InformaticsGeneva University Hospitals & Univ. of GenevaGenevaSchweiz
  3. 3.Business Information Systems, HES-SOSierreSchweiz
  4. 4.Department of Diagnostic and Interventional RadiologyUniversity Hospital AachenAachenSchweiz

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