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Content-Based Medical Image Retrieval

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Biomedical Image Processing

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Summary

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

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Authors and Affiliations

  1. University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland

    Henning Müller

  2. University and Hospitals of Geneva, Geneva, Switzerland

    Henning Müller

  3. Department of Medical Informatics, RWTH Aachen University, Aachen, Germany

    Thomas M. Deserno

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  1. Henning Müller
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  2. Thomas M. Deserno
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Correspondence to Henning Müller .

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Editors and Affiliations

  1. Inst. Medizinische Informatik, RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany

    Thomas Martin Deserno

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Müller, H., Deserno, T.M. (2010). Content-Based Medical Image Retrieval. In: Deserno, T. (eds) Biomedical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15816-2_19

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  • DOI: https://doi.org/10.1007/978-3-642-15816-2_19

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