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Abstract #3059

Handling Motion in Sparse Reconstruction with Whiskers

Jason K. Mendes1, Dennis L. Parker1

1UCAIR, University of Utah, Salt Lake CIty, UT, United States


In general, the minimum number of K-Space samples required to produce good results in sparse reconstruction is approximately four times the number of sparse coefficients. Patient motion that is neither periodic nor smooth will reduce sparsity in the temporal direction and degrade the success of the sparse reconstruction. It is therefore beneficial to detect and correct as much patient motion as possible to maximize temporal sparsity and thus reduce the total number of K-Space samples required. This is accomplished using a hybrid Radial-Cartesian sampling technique called. This sequence has an inherent ability to correct bulk patient motion and is well suited to non-linear sparse reconstruction.