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Query Expansion on Medical Image Retrieval: MeSH vs. UMLS

  • Manuel Carlos Díaz-Galiano
  • Miguel Angel García-Cumbreras
  • María Teresa Martín-Valdivia
  • L. Alfonso Ureña-López
  • Arturo Montejo-Ráez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

In this paper we explain experiments in the medical information retrieval task (ImageCLEFmed). We experimented with query expansion and the amount of textual information obtained from the collection. For expansion, we carried out experiments using MeSH ontology and UMLS separately. With respect to textual collection, we produced three different collections, the first one with caption and title, the second one with caption, title and the text of the section where the image appears, and the third one with the full text article. Moreover, we experimented with textual and visual search, along with the combination of these two results. For image retrieval we used the results generated by the FIRE software. The best results were obtained using MeSH query expansion on shortest textual collection (only caption and title) merging with the FIRE results.

Keywords

Image Retrieval Visual Result Textual Information Full Text Article Query Expansion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Manuel Carlos Díaz-Galiano
    • 1
  • Miguel Angel García-Cumbreras
    • 1
  • María Teresa Martín-Valdivia
    • 1
  • L. Alfonso Ureña-López
    • 1
  • Arturo Montejo-Ráez
    • 1
  1. 1.Computer Science Department Grupo Sistemas Inteligentes de Acceso a la InformaciónUniversity of JaénJaénSpain

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