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A Framework for the Analysis of Diffusion Compartment Imaging (DCI)

  • Maxime Taquet
  • Benoit Scherrer
  • Simon K. Warfield
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

The brain microstructure consists of the complex organization of cellular structures and extra-cellular space. Insights into this microstructure can be gained in vivo by means of diffusion-weighted imaging that is sensitive to the local patterns of diffusion of water molecules throughout the brain. Diffusion compartment imaging (DCI) provides a separate parameterization for the diffusion signal arising from each compartment of water molecules at each voxel. Their use in population studies and longitudinal monitoring of diseases hold promise for unraveling alterations of the brain microstructure in various disorders and conditions. Yet, to analyze multi-compartment models, high-level operations commonly used in scalar images need to be generalized. We present a framework that enables interpolation, averaging, filtering, spatial normalization and statistical analyses of multi-compartment data with a focus on multi-tensor representations. This framework is based on the generalization of linear combinations of voxel values through mixture simplification. We illustrate the impact of this framework in registration, atlas construction, tractography and population studies.

Keywords

Autism Spectrum Disorder Autism Spectrum Disorder Diffusion Tensor Image Complete Model Tuberous Sclerosis Complex 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Maxime Taquet
    • 1
  • Benoit Scherrer
    • 1
  • Simon K. Warfield
    • 1
  1. 1.Computational Radiology LaboratoryBoston Children’s Hospital, Harvard Medical SchoolBostonUSA

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