Theme: Shape Analysis
The anatomical structures of interest that we study within the brain are complex and need to be characterized in a consistent, reliable manner. We at UCNIA are developing methods for representing and analyzing shapes from image data to facilitate the study of anatomical changes. This also includes the development of shape alignment procedures, spatial correspondence estimation, and statistical analysis of shape parameters.
The purpose is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do global statistical analysis of brain anatomy and identify relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance.
One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images.
LV1 log Jacobians overlayed on atlas. Red denotes regions of local expansion and blue denotes regions of local contraction
See our Publications for the latest research.