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Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank

Sagar Mandava1,2, Mahesh B Keerthivasan1,2, Diego R Martin2

  • 1Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, United States of America.

Physics in Medicine and Biology
|December 17, 2020
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Summary

Non-local rank 3D (NLR3D) improves multi-contrast imaging and parameter mapping from accelerated MRI. This method enhances image quality and accuracy, especially at high acceleration rates, outperforming existing techniques.

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Reconstruction
  • Quantitative MRI

Background:

  • Subspace-constrained reconstruction methods enable accelerated MRI but often yield suboptimal image quality for certain contrasts.
  • Existing regularization techniques like joint-sparse (JS) and locally-low-rank (LLR) constraints show limitations at high acceleration rates.
  • High-quality multi-contrast imaging and parameter mapping are crucial for accurate medical diagnoses.

Purpose of the Study:

  • To introduce a novel method, non-local rank 3D (NLR3D), for high-quality recovery of subspace-coefficient images (SCI).
  • To evaluate NLR3D's performance in multi-contrast imaging and parameter mapping from accelerated MRI acquisitions.
  • To compare NLR3D against JS and LLR methods in terms of image quality and quantitative accuracy.

Main Methods:

  • NLR3D utilizes block matching and transform domain low-rank constraints for SCI recovery.
  • Performance was assessed using Monte-Carlo (MC) simulations and in vivo T2 mapping on brain and knee datasets.
  • Comparisons were made against joint-sparse (JS) and locally-low-rank (LLR) reconstruction methods.

Main Results:

  • MC simulations showed NLR3D reduced bias, variance, and mean squared error (MSE) in multi-contrast images and parameter maps compared to JS and LLR.
  • In vivo results demonstrated improved recovery of high signal-to-noise ratio (SNR) early echo time (TE) images and parameter maps at moderate and high acceleration rates.
  • No significant differences in measured T2 values were observed between NLR3D reconstructions and reference images (Wilcoxon signed rank test).

Conclusions:

  • NLR3D enables high-quality recovery of subspace-coefficient images (SCI) from accelerated MRI.
  • The method facilitates accurate multi-contrast imaging and parameter mapping, outperforming existing techniques.
  • NLR3D is a promising approach for advanced quantitative MRI applications, particularly at high acceleration factors.