This study proposes a classification framework for Alzheimer’s Disease (AD) using neuroimaging to detect structural brain alterations. It integrates multi-region analysis with displacement vector fields and Jacobian determinants. Magnetic resonance images from 432 cognitively normal (CN), 341 mild cognitive impairment (MCI), and 245 AD individuals were analyzed. Groupwise registration and deformable coregistration quantified spatial deformations and local volumetric changes. Statistical moments from displacement vector fields and Jacobian determinants enabled region-specific analysis. Stratified by sex, CN vs. AD classification achieved an AUC of 0.93 and 88.68% accuracy for males, and an AUC of 0.94 with 87.89% accuracy for females, demonstrating the efficacy of deformation-based biomarkers for AD diagnosis.