Short-axis cine cardiac MR image stacks are acquired during multiple breath-holds, which often causes a misalignment of several slices. We propose a technique for in-plane spatial realignment of motion-corrupted short-axis slices which uses probabilistic edge maps of the myocardium (generated with decision forests) as input to image registration. The proposed technique was quantitatively tested on a dataset of motion-free stacks artificially corrupted by in-plane motion. Overlap measures such as the Dice coefficient - computed on myocardial masks segmented respectively on motion-free, motion-corrupted and motion-corrected stacks - suggest that the proposed technique is able to correctly compensate for slice misalignment.
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