Amritha Nayak1, Lindsay Walker1, Carlo Pierpaoli1, The Brain Development Cooperative Group2
1NICHD, National Institutes
Multicenter DTI studies are becoming increasingly popular for their ability to improve the statistical power of a study by recruiting a large number of subjects. Data from multicenter studies can be heterogeneous in nature when no strict quality control requirements are enforced. We have designed quality assessment criteria to enable the identification of protocol errors and artifacts in multicenter DTI data, and described strategies to remediate the data to make it more compatible between sites.