Frequency Selection for the Diagnostic Characterization of Human Brain Tumours

  • Authors:
  • Carlos Arizmendi;Alfredo Vellido;Enrique Romero

  • Affiliations:
  • Dept. de Llenguatges i Sistemes Informàtics (LSI). Universitat Politècnica de Catalunya (UPC). Spain;Dept. de Llenguatges i Sistemes Informàtics (LSI). Universitat Politècnica de Catalunya (UPC). Spain;Dept. de Llenguatges i Sistemes Informàtics (LSI). Universitat Politècnica de Catalunya (UPC). Spain

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
  • Year:
  • 2009

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Abstract

The diagnosis of brain tumours is an extremely sensitive and complex clinical task that must rely upon information gathered through non-invasive techniques. One such technique is magnetic resonance, in the modalities of imaging or spectroscopy. The latter provides plenty of metabolic information about the tumour tissue, but its high dimensionality makes resorting to pattern recognition techniques advisable. In this brief paper, an international database of brain tumours is analyzed resorting to an ad hoc spectral frequency selection procedure combined with nonlinear classification.