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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.

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Keywords

accelerated acceleration acquiring acquisition applied array award axial bioengineering biomedical body channel coil combination compressed conjugated contrast decreased density diagram dimensional encoding error evaluated even excitation feasibility feet field final firstly flowchart foot full function gradient graduate grants greatly healthy helps human improve improved in vivo incoherent individual intensity interpolated introduced investigate joint knee linear maps matrix middle missed mote multiplied named neighboring noise obviously pang parallel partially pixel project proper proposed quality radiology reconstructed reconstruction reduce represents resolution samples sampling scanner scheme sense sensing sensitivity shorten significantly slice smaller space sparse strategy supported theory together variable view whole