Nonrigid motion compensation in compressed sensing reconstruction of cardiac cine MRI.

In this work, a robust nonrigid motion compensation approach, is applied to the compressed sensing reconstruction of dynamic cardiac cine MRI sequences. Respiratory and cardiac motion separation coupled with a registration algorithm is used to provide accurate reconstruction of dynamic cardiac images. The proposed scheme employs a variable splitting based optimization strategy to enable joint motion estimation along with reconstruction. We define the recovery as an energy minimization scheme utilizing an objective function that combines data consistency, spatial smoothness, and motion penalties. The validation of the proposed algorithm using numerical phantom and in-vivo cine MRI data demonstrates reconstruction of cardiac MRI data with less spatio-temporal blurring and motion artifacts from extensively under-sampled data. The proposed method is observed to provide improved reconstructions over state-of-the-art motion compensation schemes.

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