In this work, a novel method is introduced that is based on a 2-D-2-D image registration algorithm. It is embedded in an iterative algorithm for motion estimation and compensation and does not require any complex segmentation or user interaction. It is thus fully automatic, which is a very desirable feature for interventional applications. The method is evaluated on simulated and human clinical data.
Overall, it could be shown that the method can be successfully applied to a large set of clinical data without user interaction or parameter changes, and with a high robustness against initial 3-D image quality, while delivering results that are at least up to the current state of the art, and better in many cases.
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