Data driven groupwise registration of diffusion weighted images

  • Authors:
  • A. Melbourne;D. J. Hawkes;D. Atkinson

  • Affiliations:
  • Centre for Medical Image Computing, University College London;Centre for Medical Image Computing, University College London;Centre for Medical Image Computing, University College London

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

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Abstract

The acquisition of Diffusion Weighted MR images may be confounded by both patient motion and machine eddy currents, these may potentially be corrected by image registration. Two non-rigid registration schemes are compared to the result of an affine registration: a single fluid registration of the individual diffusion directions and a Progressive Principal Component Registration. All registrations are full 3D. 12 DW-MRI datasets consisting of 128×128×64 volumes from 15 diffusion directions are registered by each method and the results combined to produce fractional anisotropy maps. These maps are then inspected for improved feature appearance and fractional anisotropy variability. The affine registration demonstrates a modest improvement; image alignment by single fluid registration causes lateral brain features to appear sharper at the expense of poor deformations of the medial brain; registration by PPCR demonstrates improved contrast of lateral brain features and lower fractional anisotropy variability.