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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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