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Applications of Epsilon Radial Networks in Neuroimage Analyses

  • Nagesh Adluru
  • Moo K. Chung
  • Nicholas T. Lange
  • Janet E. Lainhart
  • Andrew L. Alexander
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7087)

Abstract

Is the brain ’wiring’ different between groups of populations?” is an increasingly important question with advances in diffusion MRI and abundance of network analytic tools. Recently, automatic, data-driven and computationally efficient framework for extracting brain networks using tractography and epsilon neighborhoods were proposed in the diffusion tensor imaging (DTI) literature [1]. In this paper we propose new extensions to that framework and show potential applications of such epsilon radial networks (ERN) in performing various types of neuroimage analyses. These extensions allow us to use ERNs not only to mine for topo-physical properties of the structural brain networks but also to perform classical region-of-interest (ROI) analyses in a very efficient way. Thus we demonstrate the use of ERNs as a novel image processing lens for statistical and machine learning based analyses. We demonstrate its application in an autism study for identifying topological and quantitative group differences, as well as performing classification. Finally, these views are not restricted to ERNs but can be effective for population studies using any computationally efficient network-extraction procedures.

Keywords

DTI brain connectivity tractography brain networks network measures classification toplogical group differences autism 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nagesh Adluru
    • 1
  • Moo K. Chung
    • 1
    • 2
  • Nicholas T. Lange
    • 3
  • Janet E. Lainhart
    • 4
  • Andrew L. Alexander
    • 1
  1. 1.Waisman CenterUniversity of Wisconsin-MadisonUSA
  2. 2.Dept. of Brain and Cog. Sci.Seoul National UniversityKorea
  3. 3.Dept. of Psychiatry and BiostatisticsHarvard UniversityUSA
  4. 4.Dept. of Psychiatry and PediatricsUniversity of UtahUSA

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