Biomedical Image Classification with Random Subwindows and Decision Trees

Raphaël Marée, Pierre Geurts, Justus Piater, Louis Wehenkel
Proc. ICCV workshop on Computer Vision for Biomedical Image Applications (CVIBA 2005), Volume 3765, page 220-229 - oct 2005
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In this paper, we address a problem of biomedical image classification that involves the automatic classification of x-ray images in 57 predefined classes with large intra-class variability. To achieve that goal, we apply and slightly adapt a recent generic method for image classification based on ensemble of decision trees and random subwindows. We obtain classification results close to the state of the art on a publicly available database of 10000 x-ray images. We also provide some clues to interpret the classification of each image in terms of subwindow relevance.

See also

The java software PiXiT implements a variant of the method proposed in this paper.

BibTex references

@InProceedings\{MGPW05b,
  author       = "Mar\'ee, Rapha{\"e}l and Geurts, Pierre and Piater, Justus and Wehenkel, Louis",
  title        = "Biomedical Image Classification with Random Subwindows and Decision Trees",
  booktitle    = "Proc.  ICCV workshop on Computer Vision for Biomedical Image Applications (CVIBA 2005)",
  series       = "LNCS",
  volume       = "3765",
  pages        = "220-229",
  month        = "oct",
  year         = "2005",
  editor       = "Y. Liu, T. Jiang, C. Zhang",
  publisher    = "Springer-Verlag",
  keywords     = "bioinformatics, machine learning",
  url          = "http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2005/MGPW05b"
}

Other publications in the database

» Raphaël Marée
» Pierre Geurts
» Justus Piater
» Louis Wehenkel