International Conference on Medical Image Computing and Computer-Assisted Intervention

MICCAI 2015: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015 pp 354-362 | Cite as

Interpolation and Averaging of Multi-Compartment Model Images

  • Renaud Hédouin
  • Olivier Commowick
  • Aymeric Stamm
  • Christian Barillot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9350)


Multi-compartment diffusion models (MCM) are increasingly used to characterize the brain white matter microstructure from diffusion MRI. We address the problem of interpolation and averaging of MCM images as a simplification problem based on spectral clustering. As a core part of the framework, we propose novel solutions for the averaging of MCM compartments. Evaluation is performed both on synthetic and clinical data, demonstrating better performance for the “covariance analytic” averaging method. We then present an MCM template of normal controls constructed using the proposed interpolation.


Spectral Cluster White Matter Microstructure Spherical Harmonic Basis Human Brain Data Orientation Distribution Func 
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

  • Renaud Hédouin
    • 1
  • Olivier Commowick
    • 1
  • Aymeric Stamm
    • 2
  • Christian Barillot
    • 1
  1. 1.VISAGES: INSERM U746, CNRS UMR6074, INRIAUniv. of Rennes IRennesFrance
  2. 2.CRL, Children’s Hospital Boston, Harvard Medical SchoolBostonUSA

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