Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images

  • Alvina Goh
  • René Vidal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3953)


We present an algebraic solution to both direct and feature-based registration of diffusion tensor images under various local deformation models. In the direct case, we show how to linearly recover a local deformation from the partial derivatives of the tensor using the so-called Diffusion Tensor Constancy Constraint, a generalization of the brightness constancy constraint to diffusion tensor data. In the feature-based case, we show that the tensor reorientation map can be found in closed form by exploiting the spectral properties of the rotation group. Given this map, solving for an affine deformation becomes a linear problem. We test our approach on synthetic, brain and heart diffusion tensor images.


Singular Value Decomposition Deformation Model Point Correspondence Single Voxel Registration Problem 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alvina Goh
    • 1
  • René Vidal
    • 1
  1. 1.Center for Imaging Science, Department of BMEJohns Hopkins UniversityBaltimoreUSA

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