Motion artifact correction of MRI via iterative inverse problem solving

Motion of the subject during magnetic resonance scan produces artifacts in the reconstructed images, which appear as blurring and ghost repetitions of the moving structures for the 2-dimensional Fourier Transform imaging methods. Several mathematical techniques have been proposed to correct the motion artifacts. Those techniques usually assume some types of motion models such as translational motion, rotational motion or linear expansion. In reality, motion can be far more complex, thus those techniques can be applied only in very limited cases. We present a new iterative algorithm to correct the corrupted data. Our method can be generalized to any arbitrary motion. The computer simulations demonstrate that a significant amount of improvement in motion artifact correction is achieved using this algorithm