Title: Nonlinear normalization methods for harmonization in neuroimaging data
Authors: Russell Shinohara - University of Pennsylvania Perelman School of Medicine (United States) [presenting]
Abstract: Magnetic resonance imaging (MRI) allows for the in vivo study of neurological and psychiatric disorders. Conventional MRI, which is widely used in both research and clinical settings, is acquired in arbitrary units and differences across scanners vary nonlinearly in volumetric and intensity space. We present and contrast statistical approaches for reducing inter-scan and inter-scanner variation for improved generalizability and comparability of MRI-based measures of volume, brain tissue integrity, and function in the presence of focal and distributed pathology.