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Similarity-Based Retrieval for Biomedical Applications

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Case-Based Reasoning on Images and Signals

Part of the book series: Studies in Computational Intelligence ((SCI,volume 73))

Summary

Similarity-based image retrieval, which has become an important area of computer vision, is a part of the case-based reasoning scenario. In similarity-based retrieval, a query image is provided and similar images from a database are retrieved, usually in order of similarity. In this chapter, we discuss the use of similarity-based retrieval for biomedical data. In particular, we describe three different applications that retrieve various types of image and signal data using similarity functions, including brain data (fMRI images and single-unit recording signals), mouse eye data (slit lens images), and skull data (CT scans). We define the similarity measures used in these applications and then discuss a unified query framework for multimedia data in general.

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Author information

Authors and Affiliations

  1. University of Washington, Seattle, WA, 98195, USA

    L. G. Shapiro, I. Atmosukarto, H. J. Lin & J. Yuen

  2. Svision, Inc., Bellevue, WA, 98006, USA

    H. Cho

  3. Children’s National Medical Center, Washington DC, 20010, USA

    S. Ruiz-Correa

Authors
  1. L. G. Shapiro
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  2. I. Atmosukarto
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  3. H. Cho
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  4. H. J. Lin
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  5. S. Ruiz-Correa
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  6. J. Yuen
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Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Arno-Nitzsche-Str.43, 04277, Leipzig, Germany

    Petra Perner

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Shapiro, L.G., Atmosukarto, I., Cho, H., Lin, H.J., Ruiz-Correa, S., Yuen, J. (2008). Similarity-Based Retrieval for Biomedical Applications. In: Perner, P. (eds) Case-Based Reasoning on Images and Signals. Studies in Computational Intelligence, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73180-1_12

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  • DOI: https://doi.org/10.1007/978-3-540-73180-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73178-8

  • Online ISBN: 978-3-540-73180-1

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