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A subspace-based coil combination method for phased-array magnetic resonance imaging.

Derya Gol Gungor1, Lee C Potter1

  • 1Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, 43210, USA.

Magnetic Resonance in Medicine
|March 17, 2015
PubMed
Summary
This summary is machine-generated.

A new coil combination method for MRI reduces image intensity inhomogeneity without needing coil sensitivity maps. This approach improves signal-to-noise and contrast, especially for severe inhomogeneity cases.

Keywords:
bias reductioncoil combinationcontrast enhancementintensity inhomogeneity correctionparallel MRIphased-array coils

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Reconstruction

Background:

  • Coil-by-coil reconstruction in MRI is followed by coil combination to create spin density maps.
  • Standard methods like sum-of-squares and adaptive combining result in spatially varying image intensity modulation.
  • Postprocessing for intensity inhomogeneity correction often fails when inhomogeneity is severe.

Purpose of the Study:

  • To introduce an alternative optimality criterion for coil combination.
  • To develop a coil combination procedure that reduces intensity inhomogeneity while preserving image contrast.

Main Methods:

  • A minimum mean squared error criterion was employed for coil combination.
  • Subspace decomposition was utilized in the coil combination process.
  • The proposed techniques were validated using both simulated and in vivo MRI data.

Main Results:

  • The new method demonstrated lower bias compared to existing techniques.
  • Experimental results showed a significant improvement in signal-to-noise ratio (approximately 7×).
  • Contrast-to-noise ratio was also enhanced (approximately 2×) in the generated images.

Conclusions:

  • The proposed coil combination method is noniterative and bypasses the need for coil sensitivity maps or image masks.
  • This approach is particularly advantageous for MRI data with severe intensity inhomogeneity.
  • The method effectively preserves image contrast while improving signal quality.