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Rapid dynamic radial MRI via reference image enforced histogram constrained reconstruction.

Thomas Gaass1, Grzegorz Bauman2, Guillaume Potdevin3

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Summary

This study introduces a novel method using composite image histograms to reduce undersampling artifacts in dynamic MRI. The technique effectively suppresses artifacts while preserving image quality and temporal resolution.

Keywords:
Dynamic MRIHistogram entropyIterative reconstructionNon-CartesianUndersampling

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging (MRI)
  • Signal Processing

Background:

  • Sub-Nyquist sampled dynamic MRI successfully suppresses undersampling artifacts using spatio-temporal redundancies.
  • However, temporally averaged and blurred composite images risk introducing false information during reconstruction.

Purpose of the Study:

  • To assess the utility of composite image histograms for measuring and suppressing undersampling artifacts in dynamic MRI.
  • To develop an algorithm that compensates for undersampling without temporal averaging, maintaining temporal resolution.

Main Methods:

  • Utilized a histogram computed from a composite image in a dynamically acquired interleaved radial MRI measurement as a reference.
  • Implemented image space regularization with a single-frame low-resolution reconstruction to ensure contrast fidelity.
  • Evaluated the approach on simulated and in vivo radial dynamic MRI acquisitions, including cardiac imaging.

Main Results:

  • The proposed algorithm effectively suppressed undersampling artifacts in dynamic MRI reconstructions.
  • Contrast properties, image details, and temporal resolution were successfully maintained.
  • Demonstrated successful application in both simulated and functional in vivo radial cardiac MRI.

Conclusions:

  • Composite image histograms offer a viable measure for assessing and suppressing undersampling artifacts in dynamic MRI.
  • The developed method provides artifact suppression without compromising essential image characteristics like contrast and temporal resolution.
  • This approach enhances the reliability of dynamic MRI reconstructions from undersampled data.