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Multimedia Retrieval in a Medical Image Collection: Results Using Modality Classes

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 7723)

Abstract

The effective communication between user and systems is one main aim in the Multimedia Information Retrieval field. In this paper the modality classification of images is used to expand the user queries within the ImageCLEF Medical Retrieval collection provided by organizers. Our main contribution is to show how and when results can be improved by understanding modality-related challenges. To do so, a detailed analysis of the results of the experiments carried out is presented and the comparison between these results shows that the improvement using modality class query expansion is query-dependent.

Keywords

  • Information Retrieval
  • Text-based Retrieval
  • Content-Based Image Retrieval
  • Merge Results Lists
  • Fusion
  • Indexing

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Castellanos, A., Benavent, X., García-Serrano, A., Cigarrán, J. (2013). Multimedia Retrieval in a Medical Image Collection: Results Using Modality Classes. In: Greenspan, H., Müller, H., Syeda-Mahmood, T. (eds) Medical Content-Based Retrieval for Clinical Decision Support. MCBR-CDS 2012. Lecture Notes in Computer Science, vol 7723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36678-9_13

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  • DOI: https://doi.org/10.1007/978-3-642-36678-9_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36677-2

  • Online ISBN: 978-3-642-36678-9

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