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NonCartesian MR image reconstruction with integrated gradient nonlinearity correction.

Shengzhen Tao1, Joshua D Trzasko2, Yunhong Shu2

  • 1Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 and Mayo Graduate School, Mayo Clinic, Rochester, Minnesota 55905.

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This summary is machine-generated.

A new non-Cartesian magnetic resonance imaging (MRI) reconstruction method corrects gradient nonlinearity (GNL) distortion during image creation. This approach reduces blurring compared to standard post-reconstruction correction, improving image clarity.

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging
  • Image Reconstruction

Background:

  • Gradient nonlinearity (GNL) in magnetic resonance imaging (MRI) causes geometrical distortion and blurring.
  • Conventional GNL correction is applied post-reconstruction, often introducing further image degradation.
  • Non-Cartesian MRI trajectories offer advantages but require sophisticated reconstruction methods.

Purpose of the Study:

  • To develop a non-Cartesian MRI reconstruction framework that prospectively corrects GNL-induced geometrical distortion.
  • To minimize image blurring associated with traditional GNL correction methods.
  • To ensure compatibility with off-resonance correction in the reconstruction process.

Main Methods:

  • A noniterative gridding-type reconstruction framework was derived, integrating GNL correction using type-III nonuniform fast Fourier transform (NUFFT).
  • A novel, numerically efficient type-III NUFFT implementation was developed.
  • Simultaneous B0 off-resonance correction was incorporated and evaluated alongside various 2D and 3D non-Cartesian acquisitions.

Main Results:

  • Both proposed and standard GNL correction methods corrected coarse-scale geometric distortion and blurring.
  • The proposed method significantly reduced blurring artifacts seen with standard correction.
  • Improved depiction of resolution inserts and enhanced clarity of small vessels were observed with the proposed GNL correction.

Conclusions:

  • The proposed GNL-integrated non-Cartesian reconstruction method effectively corrects GNL and off-resonance effects.
  • This framework mitigates resolution loss inherent in standard image-domain GNL correction.
  • The method offers improved image quality and geometrical accuracy for non-Cartesian MRI.