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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

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Published on: November 8, 2012

Quantitative assessment of motion correction for high angular resolution diffusion imaging.

Ken E Sakaie1, Mark J Lowe

  • 1Imaging Institute, The Cleveland Clinic, Mailcode U-15, Cleveland, OH 44195, USA. sakaiek@ccf.org

Magnetic Resonance Imaging
|August 22, 2009
PubMed
Summary
This summary is machine-generated.

Iterative motion correction significantly improves high angular resolution diffusion imaging (HARDI) data quality. Both tested methods outperformed no correction, with iterative approaches yielding the best results for HARDI acquisitions.

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Area of Science:

  • Neuroimaging
  • Medical Physics
  • Diffusion MRI

Background:

  • High angular resolution diffusion imaging (HARDI) is sensitive to motion artifacts.
  • Quantitative metrics for evaluating HARDI motion correction are lacking.
  • Previous studies have not extensively compared different motion correction strategies.

Purpose of the Study:

  • To compare two motion correction strategies for HARDI data.
  • To introduce quantitative metrics for assessing motion correction performance.
  • To provide a general approach for HARDI motion correction quality assurance.

Main Methods:

  • Comparison of two motion correction techniques for HARDI data.
  • Utilized two figures of merit: displacement and confidence interval of the cone of uncertainty.
  • Assessed voxel tensor uncertainty using prolate tensors.

Main Results:

  • Both motion correction methods significantly improved HARDI data compared to no correction.
  • Neither tested method showed dramatic superiority over the other.
  • Iterative application of motion correction enhanced the final results.

Conclusions:

  • Iterative motion correction is strongly recommended for HARDI data acquisition.
  • The proposed assessment approach can be broadly applied for quality assurance.
  • Motion correction is crucial for reliable HARDI data analysis.