Extensive Evaluation of Morphological Statistical Harmonization for Brain Age Prediction.

ABSTRACT: Characterizing both neurodevelopmental and aging brain structural trajectories is important for understanding normal biological processes and atypical patterns that are related to pathological phenomena. Initiatives to share open access morphological data contributed significantly to the advance in brain structure characterization. Indeed, such initiatives allow large brain morphology multi-site datasets to be shared, which increases the statistical sensitivity of the outcomes. However, using neuroimaging data from multi-site studies requires harmonizing data across the site to avoid bias. In this work we evaluated three different harmonization techniques on the Autism Brain Imaging Data Exchange (ABIDE) dataset for age prediction analysis in two groups of subjects (i.e., controls and auti

SUBMITTER: Lombardi A 

PROVIDER: S-EPMC7349402 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature