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Motion-corrected MRI with DISORDER: Distributed and incoherent sample orders for reconstruction deblurring using

Lucilio Cordero-Grande1,2, Giulio Ferrazzi2, Rui Pedro A G Teixeira1,2

  • 1Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Magnetic Resonance in Medicine
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Summary

This study introduces a new method for correcting head motion during volumetric MRI scans. This technique improves image quality for pediatric brain scans, making sedation unnecessary.

Keywords:
distributed and incoherent samplingimage reconstructionmagnetic resonancemotion correctionparallel imaging

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging

Background:

  • Volumetric MRI is crucial for anatomical brain scans.
  • Head motion during MRI can significantly degrade image quality.
  • Existing motion correction methods often require external sensors or specific sequences.

Purpose of the Study:

  • To develop a method for rigid body motion-tolerant parallel volumetric MRI.
  • To enable retrospective head motion correction across various imaging scales and sequences.
  • To improve the reliability of pediatric brain MRI examinations.

Main Methods:

  • Utilizes distributed and incoherent sampling orders for joint retrospective motion estimation and reconstruction.
  • Leverages encoding redundancy inherent in coil arrays for motion resilience.
  • Does not require external sensors, navigators, or training data, applicable to 3D encoding sequences.

Main Results:

  • Simulations demonstrate effective inter-shot corrections for typical in vivo motion levels.
  • Feasibility of inter- and intra-shot corrections shown under controlled in vivo motion.
  • High-quality results achieved in corrupted volumes from clinical pediatric examinations.

Conclusions:

  • The proposed framework effectively addresses rigid motion in volumetric brain scans.
  • Sufficient encoding redundancy enables reliable pediatric examinations without sedation.
  • The method offers a robust solution for motion-corrupted MRI data.