Shujing Cao1, Feng
Huang2, Rui Li1, Chun Yuan3
1Center
for Biomedical Imaging Research, Department of Biomedical Engineering, School
of Medicine, Tsinghua University, Beijing, China; 2Philips
Healthcare, Beijing, China; 3Department of Radiology, University
of Washington, Seattle, WA, United States
A new retrospective motion compensation method named as GeneRAlized Multiple Averages (GRAMA) is proposed. GRAMA synthesizes two copies of original k-space with relative consistency using a couple of optimized convolution kernel. Based on the interleaved data acquisition manner, error in different k-space copies is inherent. Instead of average with original k-space like that in conventional multiple averages method, GRAMA directly use the average of two synthetic k-space to reconstruct motion corrected image. Volunteer experiments indicate GRAMA effectively balances SNR preservation and artifact reduction.
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