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Cross-sectional analysis of longitudinal anatomical magnetic resonance imaging (MRI) data may be suboptimal as each dataset is analyzed independently. In this study, we evaluate how much variability can be reduced by analyzing structural volume changes in longitudinal data using longitudinal analysis. We propose a two-part pipeline that consists of longitudinal registration and longitudinal classification...
We used cross-sectional tensor-based morphometry to visualize reduced volume in the whole brains of pediatric patients with multiple sclerosis, relative to healthy controls. As a marker of local volume difference, we used the Jacobian determinant of the deformation field that maps each subject to a standard space. To properly assess abnormal differences in volume in this age group, it is necessary...
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