Abstract #3059

Jason K.
Mendes^{1}, Dennis L. Parker^{1}

^{1}UCAIR,

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.