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Related Experiment Videos

Frequency-domain simulation of MR tagging

W R Crum1, E Berry, J P Ridgway

  • 1Centre of Medical Imaging Research, University of Leeds, UK.

Journal of Magnetic Resonance Imaging : JMRI
|October 24, 1998
PubMed
Summary

This study introduces an improved simulation model for magnetic resonance (MR) tagged images, enhancing the tracking of myocardial motion. The new model accurately simulates tagged images by addressing limitations in existing methods.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Science

Background:

  • Magnetic Resonance (MR) image simulation aids sequence development and understanding image formation.
  • MR tagging is crucial for tracking myocardial motion but faces challenges with spatial-domain methods.
  • Existing frequency-domain models are inadequate for simulating tagged MR images.

Purpose of the Study:

  • To develop an accurate simulation model for MR tagged images.
  • To address limitations of existing models in representing motion artifacts and signal wrap.
  • To improve the simulation of myocardial motion tracking using MR tagging.

Main Methods:

  • An extended frequency-domain model based on Bloch equations and the Fourier shift theorem was developed.

Related Experiment Videos

  • The new model corrects inaccuracies in simulating tagged MR images.
  • Software was created to generate ideal tag intensity profiles and simulate tagged images.
  • Main Results:

    • The extended model accurately simulates tagged MR images, overcoming limitations of previous methods.
    • Shifted k-space patterns in tagged images and their dependence on binomial tagging sequence order were elucidated.
    • A novel application of the Fourier shift theorem enables faster simulation of static tagged images.

    Conclusions:

    • The developed model provides accurate simulation of MR tagged images for myocardial motion analysis.
    • The findings enhance the utility of MR tagging in offline sequence development and research.
    • The study offers a more efficient approach to simulating static tagged MR images.