Autofocusing of clinical shoulder MR images for correction of motion artifacts

Abstract

A post-processing ”autofocusing” algorithm for the reduction of motion artifacts in MR images has been developed and tested on a large clinical data set of high resolution shoulder images. The algorithm uses only the raw (complex) data from the MR scanner, and requires no knowledge of the patient motion during the scan, deducing that from the raw data itself. It operates by searching over the space of possible patient motions and optimizing the image quality. Evaluation of this technique on the clinical data set (for which navigator echo based measured motions and corrected images were available) show that the algorithm can correct for the effects of global translation during the scan almost as well as the navigator echo approach and is more robust.

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