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Rigid motion correction for magnetic resonance fingerprinting with sliding-window reconstruction and image

Zhongbiao Xu1, Huihui Ye2, Mengye Lyu3

  • 1Key Laboratory of Mental Health of the Ministry of Education, School of Biomedical Engineering, Southern Medical University, Guangzhou, China; School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.

Magnetic Resonance Imaging
|November 16, 2018
PubMed

Insights

Patient motion during magnetic resonance fingerprinting (MRF) causes artifacts. This study introduces a novel motion correction technique for MRF, significantly reducing blurring and improving the accuracy of parameter maps.

Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Imaging

Background:

  • Magnetic resonance fingerprinting (MRF) enables simultaneous multi-parameter mapping using a single pulse sequence.
  • Patient motion during MRF acquisition is a significant challenge, leading to image blurring and artifacts in quantitative parameter maps.

Purpose of the Study:

  • To develop and evaluate a novel method for correcting rigid motion in MRF data.
  • To improve the accuracy and quality of MRF-derived parameter maps (T1, T2, proton density) in the presence of motion.

Main Methods:

  • A sliding-window reconstruction approach was employed to generate intermediate MRF images.
  • Image registration techniques were utilized to estimate rigid motion parameters between these intermediate images.
  • Motion-corrupted k-space data were corrected using estimated motion parameters, followed by conventional MRF reconstruction.

Main Results:

  • The proposed motion correction method effectively reduced blurring and artifacts in brain T1, T2, and proton density maps.
  • Normalized root-mean-square error was significantly lower for motion-corrected MRF compared to uncorrected MRF.
  • Evaluations included both simulated and in vivo MRF experiments with various induced motion types.

Conclusions:

  • The developed motion correction technique demonstrates the potential for producing accurate MRF parameter maps.
  • This method offers a viable solution for mitigating the impact of in-plane rigid motion in MRF acquisitions.
Keywords:
Image registrationMagnetic resonance fingerprintingMotion correctionSliding-window reconstruction

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