Analysis with Multivariate Tensor-Based Morphometry in 829 ADNI subjects

• As the widely used way to find candidate biomarkers of disease progression, computational anatomy methods are usually applied to map the profile of disease effects on the brain and model the localized changes in Alzheimer’s disease (AD). • We propose a new framework of cortical surface morphometry analysis based on FreeSurfer and multivariate tensor-based morphometry (MTBM) associated with 829 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). • With the effective segmentation accuracy of FreeSurfer’s and strong statistics ability of MTBM, the proposed framework shows a powerful performance on detecting localized anatomical differences on cortical surface in ADNI database.