A0432
Title: Longitudinal elastic shape analysis of surfaces
Authors: Yuexuan Wu - University of Washington (United States) [presenting]
Abstract: Over the past 30 years, magnetic resonance imaging (MRI) has become a ubiquitous tool for accurately visualizing the development of subcortical structures in the brain. However, the quantification of complex subcortical structures is still in its infancy due to challenges in shape extraction, representation, and modelling. A simple and efficient framework of longitudinal elastic shape analysis (LESA) is introduced for subcortical structure surfaces. Integrating ideas from elastic shape analysis of static surfaces and statistical modelling of sparse longitudinal data, LESA provides a set of tools for systematically quantifying longitudinal changes in subcortical surface shapes from raw structural MRI data. LESA can efficiently represent complex subcortical structures using a small number of basis functions and can accurately predict the spatiotemporal shape changes of the surfaces. Besides, by applying LESA to analyze three longitudinal neuroimaging data sets, its wide applications are showcased in estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups.
