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Putting the Content Into Context: Features and Gaps in Image Retrieval

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  • Henning Müller

    (University and Hospitals of Geneva and University of Applied Sciences, Switzerland)

  • Jayashree Kalpathy-Cramer

    (Oregon Health and Science University, USA)

Abstract

Digital management of medical images is becoming increasingly important as the number of images being created in medical settings everyday is growing rapidly. Content-based image retrieval or techniques based on the query-by-example paradigm have been studied extensively in computer vision. However, the global, low level visual features automatically extracted by these algorithms do not always correspond to high level concepts that a user has in his mind for searching. The role of image retrieval in diagnostic medicine can be quite complex, making it difficult for the user to express his/her information needs appropriately. Image retrieval in medicine needs to evolve from purely visual retrieval to a more holistic, case-based approach that incorporates various multimedia data sources. These include multiple images, free text, structured data, as well as external knowledge sources and ontologies.

Suggested Citation

  • Henning Müller & Jayashree Kalpathy-Cramer, 2009. "Putting the Content Into Context: Features and Gaps in Image Retrieval," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 4(1), pages 88-98, January.
    • Handle: RePEc:igg:jhisi0:v:4:y:2009:i:1:p:88-98
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