Self-calibrated radial sampling parallel imaging reconstruction with iterative k-x estimation
Yi-Cheng Hsu 1 , Ying-Hua Chu 1 , and Fa-Hsuan Lin 1
Institute of Biomedical Engineering,
National Taiwan University, Taipei, Taiwan
We propose an iterative k-x method to estimate weights
to reconstruct missing radial sampling k-space data
points using individually reconstructed coil images from
the under-sampled data directly. Once missing k-space
data were estimated, individually reconstructed coil
images used in the last estimation were replaced by coil
images in this reconstruction for the next iteration.
Our method can successfully reconstruct human brain
images with 2 mm spatial resolution and minimal
streaking artifacts using 22 radial projections at 3T
using a 32-channel head coil array.
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