Query and Document Expansion with Medical Subject Headings Terms at Medical Imageclef 2008

  • Julien Gobeill
  • Patrick Ruch
  • Xin Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)


In this paper, we report on query and document expansion using Medical Subject Headings (MeSH) terms designed for medical ImageCLEF 2008. In this collection, MeSH terms describing an image could be obtained in two different ways: either being collected with the associated MEDLINE’s paper, or being extracted from the associated caption. We compared document expansion using both. From a baseline of 0.136 for Mean Average Precision (MAP), we reached a MAP of respectively 0.176 (+29%) with the first method, and 0.154 (+13%) with the second. In-depth analyses show how both strategies were beneficial, as they covered different aspects of the image. Finally, we combined them in order to produce a significantly better run (0.254 MAP, +86%). Combining the MeSH terms using both methods gives hence a better representation of the images, in order to perform document expansion.


Cross-Language Image Retrieval Text Categorization Query Expansion Document Expansion 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Julien Gobeill
    • 1
  • Patrick Ruch
    • 1
  • Xin Zhou
    • 1
  1. 1.Service d’Informatique MédicaleUniversity and Hospitals of GenevaGenèveSwitzerland

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