Bing Wu1, Chunlei Liu1
1Brain Imaging and Analysis Center, School
of Medicine, Duke University, Durham, NC, United States
The
conventional approach of deriving coil sensitivity profile for SENSE
reconstruction using a small number of auto-calibration scan lines limits the
fidelity of the coil sensitivity estimate, and hence the quality of SENSE
reconstructions. However estimating
coil sensitivity from under-sampled k-space data set is an under-determined
problem, and previous attempts resort to additional regularizing terms that
may affect the accuracy of the outcome. We present a new compress sensing
based approach that allows the coil sensitivity profile to be estimated using
all the acquired data measurements to achieve improved coil sensitivity
estimate, which in turn leads to an improved SENSE reconstruction.