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Abstract #3761

Generalized Multiple Averages (GRAMA) for Motion Compensation

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.