Graph wavelet applied to human brain connectivity

Pierre Besson*, Christine Delmaire, Vianney Le Thuc, Stéphane Lehéricy, Florence Pasquier, Xavier Leclerc

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The graph theory is increasingly used and provides powerful tools for studying complex biological networks problems. They were able to characterize the small-worldness of the brain connectivity network and were accurate enough to observe topological differences between healthy and diseased brain graphs. However, these methods relied on topological characteristics implying that differences could be observed between two groups only if corresponding graphs topologies were different. In this paper, we developed a multiscale method to characterize fine to coarse brain connectivity, which allows to observe connectivity differences between two groups even if corresponding graphs topologies are identical. For this purpose, we defined a new wavelet graph transform based on the interval wavelet transform. Our method decomposes the connectivity values of a graph regardless of its topology, can be defined with a large spectrum of wavelet bases and is invertible. Finally, we applied our graph wavelet decomposition on brain connectivity graph in a group of healthy controls.

Original languageEnglish (US)
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages1326-1329
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: Jun 28 2009Jul 1 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
CountryUnited States
CityBoston, MA
Period6/28/097/1/09

Keywords

  • Brain
  • Graph theory
  • Magnetic resonance imaging
  • Networks
  • Wavelet transforms

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Graph wavelet applied to human brain connectivity'. Together they form a unique fingerprint.

Cite this