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A Method for Registering Diffusion Weighted Magnetic Resonance Images

  • Xiaodong Tao
  • James V. Miller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

Diffusion weighted magnetic resonance (DWMR or DW) imaging is a fast evolving technique to investigate the connectivity of brain white matter by measuring the self-diffusion of the water molecules in the tissue. Registration is a key step in group analysis of the DW images that may lead to understanding of functional and structural variability of the normal brain, understanding disease process, and improving neurosurgical planning. In this paper, we present a new method for registering DW images. The method works directly on the diffusion weighted images without using tensor reconstruction, fiber tracking, and fiber clustering. Therefore, the performance of the method does not rely on the accuracy and robustness of these steps. Moreover, since all the information in the original diffusion weighted images is used for registration, the results of the method is robust to imaging noise. We demonstrate the method on intra-subject registration with an affine transform using DW images acquired on the same scanner with the same imaging protocol. Extension to deformable registration for images acquired on different scanners and/or with different imaging protocols is also discussed.

Keywords

Fractional Anisotropy Diffusion Weighted Image Diffusion Weight Magnetic Resonance Image Brain White Matter Deformable Registration 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaodong Tao
    • 1
  • James V. Miller
    • 1
  1. 1.GE ResearchNiskayunaUSA

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