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PEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction
Yilong Liu1,2, Mengye Lyu1,2, Markus Barth3
1Laboratory of Biomedical Imaging and Signal Processing, the University of Hong Kong, Hong Kong SAR, People's Republic of China.
Phase error correction GRAPPA (PEC-GRAPPA) enables robust simultaneous multislice (SMS) EPI reconstruction by correcting Nyquist ghosts in k-space. This method avoids cumbersome manual tuning, offering a practical solution for improved image quality.
Area of Science:
- Magnetic Resonance Imaging
- Medical Physics
- Biomedical Engineering
Background:
- Simultaneous multislice (SMS) Echo Planar Imaging (EPI) accelerates MRI acquisition.
- Nyquist ghosts are artifacts in SMS EPI that degrade image quality.
- Existing methods like 2D phase error correction SENSE (PEC-SENSE) require cumbersome manual adjustments.
Purpose of the Study:
- To develop a robust k-space implementation of phase error correction for SMS EPI.
- To improve Nyquist ghost correction without manual tuning.
- To introduce PEC-GRAPPA as a practical alternative to PEC-SENSE.
Main Methods:
- Extended PEC-SENSE to k-space, creating PEC-GRAPPA.
- Incorporated singular value shrinkage into virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) to avoid empirical rank selection.
- Evaluated PEC-GRAPPA against PEC-SENSE and 1D linear phase correction GRAPPA using phantom and human brain data.
Main Results:
- PEC-GRAPPA effectively reconstructed SMS EPI images, removing phase error artifacts.
- Achieved comparable residual artifact levels and temporal signal-to-noise ratio (SNR) to carefully tuned PEC-SENSE.
- Outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA.
Conclusions:
- PEC-GRAPPA provides robust and practical SMS EPI reconstruction with effective Nyquist ghost correction.
- Eliminates the need for cumbersome tuning and masking procedures.
- Facilitates slice-dependent 2D Nyquist ghost correction in k-space for SMS EPI.
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