Rachel Wai-chung Chan1, Elizabeth Anne
Ramsay2, Donald Bruce Plewes2
1Medical Biophysics, University of
Toronto, Toronto, ON, Canada; 2Imaging Research, University of
Toronto, Toronto, ON, Canada
Adaptive
radial imaging allows multiple images to be retrospectively reconstructed
from the same dataset, each with a different spatial-temporal balance. It has
been shown that compressed sensing reconstruction can be used reduce streak
artifacts in high-temporal-resolution images created by radial undersampling.
Here, we compare the effect of 3 adaptive sampling schemes (golden angle,
bit-reversed, and random sampling scheme) on the ability of CS reconstruction
to reduce streak artifacts, at various spatiotemporal resolutions. Results
show that CS reconstruction lowers the degree of error and mostly preserves
the differences among sampling schemes compared to Fourier reconstruction.