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A generalized approach to parallel magnetic resonance imaging.

D K Sodickson1, C A McKenzie

  • 1Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. dsodicks@caregroup.harvard.edu

Medical Physics
|September 11, 2001
PubMed
Summary

Parallel magnetic resonance (MR) imaging accelerates scans using multiple coils. New generalized methods and conditioning techniques improve image quality and robustness, enabling higher acceleration rates.

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Area of Science:

  • Medical Imaging
  • Physics
  • Engineering

Background:

  • Parallel magnetic resonance (MR) imaging accelerates data acquisition by using multiple radiofrequency detector coils.
  • Existing parallel imaging techniques like SMASH and SENSE have limitations in performance and robustness.

Purpose of the Study:

  • To derive a generalized formulation for parallel MR imaging.
  • To develop new algorithms and hybrid reconstruction approaches for improved performance.
  • To enhance the practical robustness of parallel image reconstructions.

Main Methods:

  • A generalized mathematical framework for parallel MR imaging was developed.
  • Hybrid reconstruction algorithms combining SMASH-like and SENSE-like methods were constructed.
  • Numerical conditioning techniques were incorporated to improve reconstruction robustness and eliminate sensitivity calibration steps.

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Main Results:

  • The generalized formulation unified existing parallel imaging techniques and suggested novel algorithms.
  • Hybrid approaches with numerical conditioning demonstrated improved performance and robustness.
  • The methods extended the range of accelerations for obtaining high-quality parallel MR images.

Conclusions:

  • The generalized formulation provides a unified view of parallel MR imaging techniques.
  • Hybrid reconstruction strategies combined with numerical conditioning significantly enhance parallel imaging capabilities.
  • These advancements enable higher acceleration factors for faster, high-quality MR imaging.