Magnetic Resonance Imaging (MRI) provides a unique opportunity to investigate neural
changes in healthy and clinical conditions. Its large inherent susceptibility to motion,
however, often confounds the measurement. Approaches assessing, correcting, or preventing
motion corruption of MRI measurements are under active development, and such efforts
can greatly benefit from carefully controlled datasets. We present a unique dataset
of structural brain MRI images collected from 148 healthy adults which includes both
motion-free and motion-affected data acquired from the same participants. This matched
dataset allows direct evaluation of motion artefacts, their impact on derived data,
and testing approaches to correct for them. Our dataset further stands out by containing
images with different levels of motion artefacts from the same participants, is enriched
with expert scoring characterizing the image quality from a clinical point of view
and is also complemented with standard image quality metrics obtained from MRIQC.
The goal of the dataset is to raise awareness of the issue and provide a useful resource
to assess and improve current motion correction approaches.
