Frequency selection for the diagnostic characterization of human brain tumours

Carlos Arizmendi, Alfredo Vellido, Enrique Romero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Pages391-398
Number of pages8
Edition1
ISBN (Print)9781607500612
DOIs
StatePublished - 2009
Externally publishedYes

Publication series

NameFrontiers in Artificial Intelligence and Applications
Number1
Volume202
ISSN (Print)0922-6389

Keywords

  • Artificial Neural Networks
  • Brain Tumour
  • Magnetic Resonance Spectroscopy
  • Moving Window

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