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In-plane "superresolution" MRI with phaseless sub-pixel encoding.

Franciszek Hennel1, Rui Tian1, Maria Engel1

  • 1Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.

Magnetic Resonance in Medicine
|April 16, 2018
PubMed
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This study introduces a novel superresolution MRI technique using microscopic tagging, overcoming phase fluctuation issues in multi-shot MRI. This method enables artifact-free, high-resolution diffusion-weighted imaging, even with patient motion.

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Image Reconstruction
  • Biomedical Engineering

Background:

  • Multi-shot MRI acquisition is hindered by sensitivity to transverse magnetization phase fluctuations.
  • Existing methods struggle to achieve high-resolution imaging without phase-related artifacts.

Purpose of the Study:

  • To develop a superresolution MRI method robust to phase fluctuations.
  • To enable artifact-free, high-resolution imaging in challenging conditions like diffusion-weighted MRI.

Main Methods:

  • Utilized microscopic tagging, analogous to optical structured illumination, for subpixel resolution.
  • Implemented phaseless modulation to discard phase fluctuations during reconstruction.
  • Applied field map-based phase correction and adapted filtering to mitigate distortions and ringing artifacts.
Keywords:
MRIdiffusion imagingphase sensitivityspatial encodingstructured illuminationsuperresolution

Related Experiment Videos

Main Results:

  • Achieved artifact-free superresolution images despite tagging sequence duration and distortions.
  • Successfully obtained high-resolution diffusion-weighted images of the human head using a three-shot EPI sequence.
  • Demonstrated robustness against motion-related phase fluctuations.

Conclusions:

  • Tagging-based sub-pixel encoding offers a viable alternative to k-space segmenting in the presence of phase fluctuations.
  • The proposed improvements make this superresolution MRI technique practical for real-world applications, especially in diffusion imaging.
  • This method is particularly advantageous for imaging under strong diffusion gradients where motion artifacts are common.