A key challenge in robustly extracting quantitative information from MRI data is the dependence of derived features on nuisance factors, such as the scanning protocol, hardware and software, which are different between vendors and vary with site. While there exist several harmonisation approaches, what’s missing is objective ways and datasets to compare them. Here we present a novel multi-modal neuroimaging data resource for evaluating and comparing harmonisation approaches based on a “travelling heads” paradigm. We further demonstrate how such a resource can be used to a) map the need for harmonisation for different imaging-derived features, b) evaluate existing harmonisation approaches.
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