Demons registration of high angular resolution diffusion images

  • Authors:
  • Luke Bloy;Ragini Verma

  • Affiliations:
  • Department of Bioengineering, University of Pennsylvania;Department of Radiology, University of Pennsylvania

  • Venue:
  • ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
  • Year:
  • 2010

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Abstract

In this work we present a method for non-rigid registration of high angular resolution diffusion imaging (HARDI) datasets that are modeled by a field of antipodally symmetric spherical functions, represented by their expansion in the real spherical harmonic (RSH) basis. We use a multichannel demons algorithm which utilizes a computationally simple, rotationally invariant similarity function defined in the RSH space. Additionally, we describe a finite strain based algorithm for reorientation of the HARDI data model. We validate our framework on simulated fiber orientation distribution datasets and on human in-vivo data.