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Related Experiment Videos

Optimization of sensitivity encoding with arbitrary k-space trajectories.

Mark Bydder1, Joanna E Perthen, Jiang Du

  • 1Department of Radiology, MRI3 Research, University of California San Diego, San Diego, CA 92103-8226, USA. mbydder@ucsd.edu

Magnetic Resonance Imaging
|October 2, 2007
PubMed
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This study introduces a simple method for setting regularization parameters in Sensitivity Encoding (SENSE) MRI. It also explores density weighting and intensity correction to improve image reconstruction quality.

Area of Science:

  • Magnetic Resonance Imaging
  • Image Reconstruction

Background:

  • Sensitivity Encoding (SENSE) is a key magnetic resonance imaging technique.
  • SENSE image reconstruction involves solving an ill-conditioned inverse problem, often requiring regularization and preconditioning.

Purpose of the Study:

  • To propose a straightforward heuristic for determining the regularization parameter in SENSE.
  • To discuss density weighting and intensity correction as preconditioning methods.
  • To examine the influence of coil sensitivity estimation on regularization.

Main Methods:

  • Development of a heuristic for regularization parameter selection.
  • Evaluation of density weighting and intensity correction as preconditioners.
  • Analysis of coil sensitivity estimation's role in regularization.

Related Experiment Videos

  • Proposal of a modified intensity correction for phase-constrained SENSE.

    • Main Results:

    • A simple heuristic is suggested for regularization parameter determination.
    • Density weighting and intensity correction are discussed as effective preconditioners.
    • The impact of coil sensitivity estimation on regularization is analyzed.
    • A modified intensity correction method is presented for phase-constrained SENSE.

    Conclusions:

    • The proposed heuristic offers a practical approach to regularization parameter selection in SENSE.
    • Preconditioning techniques like density weighting and intensity correction enhance SENSE reconstruction.
    • Coil sensitivity estimation plays a crucial role in SENSE regularization.
    • The modified intensity correction improves SENSE performance with phase constraints.