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The MedGIFT Group at ImageCLEF 2008

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

Abstract

This article describes the participation of the MedGIFT research group at the 2008 ImageCLEFmed image retrieval benchmark. We concentrated on the two tasks concerning medical imaging. The visual information analysis is mainly based on the GNU Image Finding Tool (GIFT). Other information such as textual information and aspect ratio were integrated to improve our results. The main techniques are similar to past years, with tuning a few parameters to improve results.

For the visual tasks it becomes clear that the baseline GIFT runs do not have the same performance as some more sophisticated and more modern techniques. GIFT can be seen as a baseline for the visual retrieval as it has been used for the past five years in ImageCLEF. Due to time constraints not all optimizations could be performed and no relevance feedback was used, one of the strong points of GIFT. Still, a clear difference in performance can be observed depending on the various optimizations applied, and the difference with the best groups is smaller than in past years.

Keywords

Image Retrieval Text Retrieval Pattern Recognition Letter Wild Card Histogram Intersection 
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

  • Xin Zhou
    • 1
  • Julien Gobeill
    • 1
  • Henning Müller
    • 1
    • 2
  1. 1.Geneva University Hospitals and University of GenevaSwitzerland
  2. 2.University of Applied Sciences Western Switzerland, SierreSwitzerland

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