We investigated the artifacts arising from different types of head motion during brain structural MR imaging and how well these artifacts can be compensated for using retrospective correction based on two different motion-tracking techniques: FatNavs and Tracoline systems. High image quality could be recovered in our slow-motion scenarios using both motion estimation techniques. Masking the non-rigid part of the neck during FatNav volumes registration led to higher image quality when large pitch-motion was present. The fast continuous motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used.
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