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Abstract #2686

Interpolated Parallel Imaging Compressed Sensing

Yong Pang1, Xiaoliang Zhang1, 2

1Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States; 2UC Berkeley/UCSF Joint Graduate Group in Bioengineering, Berkeley & San Francisco, CA, United States

In this project, we combined the parallel imaging with the interpolated compressed sensing (iCS) method to further accelerate the imaging speed for multi-slice 2-dimensional parallel MR imaging. The raw data of each slice from each channel is multiplied by a weighting function and then used to estimate the missed k-space data of the neighboring slice from the same array channel, which helps improve the image quality of the neighboring slice. In-vivo MR of human has been used to investigate the feasibility of the proposed method, showing obviously increased SNR and CNR.