  Motion free reconstruction of compressively sampled cardiac perfusion MR
images is a challenging problem. It is due to the aliasing artifacts and the
rapid contrast changes in the reconstructed perfusion images. In addition to
the reconstruction limitations, many registration algorithms under perform in
the presence of the rapid intensity changes. In this paper, we propose a novel
motion correction method that reconstructs the motion free image series from
the undersampled cardiac perfusion MR data. The motion correction method uses
the novel robust principal component analysis based reconstruction along with
the periodic decomposition to separate the respiratory motion component that
can be registered, from the contrast intensity variations. It is tested on
simulated data and the clinically acquired data. The performance of the method
is qualitatively assessed and compared with the existing motion correction
methods. The proposed method is validated by comparing manually acquired
time-intensity curves of the myocardial sectors to automatically generated
curves before and after registration.

Image and Video Processing;Medical Physics