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Improving Non-Cartesian MRI Reconstruction through Discontinuity Subtraction.

Jiayu Song1, Qing Huo Liu

  • 1Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA ; Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC 27710, USA.

International Journal of Biomedical Imaging
|November 21, 2012
PubMed
Summary

This study introduces a new method to reduce artifacts in fast MRI scans using non-Cartesian sampling. The technique effectively minimizes image distortions, improving overall quality, especially with undersampled data.

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Area of Science:

  • Medical Imaging
  • Image Reconstruction
  • Magnetic Resonance Imaging

Background:

  • Non-Cartesian sampling accelerates Magnetic Resonance Imaging (MRI) but poses reconstruction challenges.
  • Conventional methods often produce artifacts like ringing and streaking due to image discontinuities.
  • Accurate and fast reconstruction from non-Cartesian k-space data is a significant research area.

Purpose of the Study:

  • To analyze the point spread function (PSF) of non-Cartesian reconstruction.
  • To propose and evaluate a novel leakage reduction reconstruction scheme based on discontinuity subtraction.
  • To improve image quality from fast MRI scans with non-Cartesian sampling.

Main Methods:

  • Analysis of the principal point spread function (PSF) for non-Cartesian reconstruction.
  • Development of a discontinuity subtraction-based scheme for leakage reduction.
  • Utilization of multidimensional nonuniform fast Fourier transform (NUFFT) for simulation and reconstruction.
  • Enforcement of data fidelity in k-space during iterative reconstruction.

Main Results:

  • The proposed method effectively reduces artifacts caused by high image discontinuities.
  • Improved image quality was observed for reconstructions from undersampled non-Cartesian data.
  • The scheme demonstrated utility across various non-Cartesian sampling trajectories (2D spiral, 2D/3D radial).

Conclusions:

  • The discontinuity subtraction method offers a viable solution for artifact reduction in non-Cartesian MRI.
  • This approach enhances the quality and reliability of fast MRI reconstructions.
  • The findings are applicable to diverse non-Cartesian sampling strategies and undersampled datasets.