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Related Experiment Videos

Characterization of and correction for eddy current artifacts in echo planar diffusion imaging

P Jezzard1, A S Barnett, C Pierpaoli

  • 1Unit on MRI Physics, Laboratory of Brain and Cognition, NIMH, National Institutes of Health, Bethesda, Maryland, USA.

Magnetic Resonance in Medicine
|May 15, 1998
PubMed
Summary

This study introduces a new method to correct geometric distortions in magnetic resonance diffusion imaging caused by eddy currents. The technique significantly reduces artifacts, improving the quality of diffusion tensor maps for better tissue characterization.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Neuroimaging

Background:

  • Magnetic resonance diffusion imaging (DI) is crucial for noninvasive tissue characterization.
  • DI is susceptible to artifacts, particularly eddy current-induced geometric distortions, which compromise clinical utility.
  • These distortions arise from misalignments in diffusion-weighted images, affecting diffusion parameter maps.

Purpose of the Study:

  • To address and correct eddy current-induced geometric distortions in echo planar diffusion imaging.
  • To present a novel approach for characterizing and calibrating eddy current effects.
  • To improve the accuracy and reliability of diffusion imaging data.

Main Methods:

  • A new method was developed to characterize and calibrate eddy current effects.

Related Experiment Videos

  • Correction involves acquiring one-dimensional field maps for each slice and diffusion step.
  • The approach is applied to interleaved echo planar diffusion images.

    • Main Results:

    • The proposed eddy current correction scheme effectively eliminates geometric distortions in diffusion-weighted images.
    • Significant improvements were observed in the quality of computed diffusion tensor maps.
    • Artifacts in diffusion imaging of the human brain were substantially reduced.

    Conclusions:

    • The developed method successfully corrects eddy current-induced artifacts in diffusion imaging.
    • This technique enhances the diagnostic value of magnetic resonance diffusion imaging.
    • Improved diffusion tensor maps provide more reliable information for clinical applications.