Motion-induced artefacts in MRI are a common occurrence but can obscure pathologies or be falsely identified as pathological. Reacquiring motion-corrupted scans is expensive, and thus retrospective and prospective motion correction methods have been introduced. Although motion correction shows promise, there is a lack of exhaustive testing on its efficacy with respect to full clinical cerebral MRI protocols. Here we present a dataset (n = 22) to facilitate future research, which includes data with and without intentional motion, and with and without prospective motion correction, across six MRI sequences included in a full clinical cerebral MRI protocol. Motion was captured by an external tracking device, and the dataset includes the motion data as derived motion transforms. For standardization, all image data are fully BIDS-compliant. Raw k-space data are available as well. As the dataset pairs motion-free data with motion-corrupted data, it can be used to develop or test different motion-correction or k-space reconstruction methods.
Madsen et al. (Thu,) studied this question.
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