Functional Analysis of Tracted-Based Diffusion Tensors

• Activity Number: 502
• Type: Topic Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Hongtu Zhu*+ and Martin Styner and John H. Gilmore
• Companies: The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
• Keywords: functional data analysis ; varying coefficient model ; local polynomial ; test statistics ; diffusion tensor

Abstract

This paper presents a functional regression framework, called VCMTS, for the analysis of multiple diffusion properties along fiber bundle and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The functional regression framework consists of four integrated components: a varying coefficient model for characterizing the association between fiber bundle diffusion properties and a set of covariates, the local polynomial kernel method for estimating smoothed multiple diffusion properties along individual fiber bundles, a global test statistic for testing hypotheses of interest, and a resampling method for approximating the $p-$value of the global test statistic. The proposed methodology is applied to a clinical study of neurodevelopment.