Abstract #2684
Motion Compensated Free Breathing Myocardial Perfusion MRI Using Iterative Non Local Shrinkage
Yasir Q Mohsin 1 , Sajan Goud Lingala 2 , Edward DiBella 3 , and Mathews Jacob 1
1
Electrical Engineering, University of Iowa,
Iowa city, IA, United States,
2
Electrical
Engineering, University of Southern California, Los
Angeles, California, United States,
3
Department
of Radiology, University of Utah, S.L.City,UT, United
States
We recover myocardial perfusion imaging (MPI) data from
undersampled measurements. We are concerned to address
the issues related to the motion compensation of the MRI
images when the interframe motion is considerably high
and that the current CS schemes often result in
unacceptable spatio-temporal blurring and residual alias
artifacts in the presence of respiratory motion and
cardiac motion due to inaccurate gating. The current
ME-MC schemes have been shown to improve the results but
they are usually slow in implementation and come up with
considerably increased computational complexity. A
challenging problem when non-convex functions are
involved in the recon while we use continuation to
address the local minima issues. Our framework does not
require the motion parameters to be explicitly
estimated, and hence is considerably more efficient than
explicit ME-MC schemes.
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