The Department of Mathematics & Statistics is delighted to welcome alumna Gina-Maria Pomann, who is a Senior Biostatistician and the Manager of the Duke Translational Medicine Institute Biostatistics Core. Gina-Maria earned her PhD in Statistics from North Carolina State University where she was an AT&T and National Science Foundation graduate research fellow. Her primary interests are in image analysis, functional data, case-control sampling, observational data, statistical education, and promoting diversity.
Title: Statistical Image Analysis for the Study of Multiple Sclerosis
Date: Wednesday, November 29th at 11:00 am
Location: SCP 117
A number of magnetic resonance (MR) imaging modalities can be used to measure the diffusion of water in the brain. An important question is which of these modalities are most useful for differentiating between MR images of patients with multiple sclerosis (MS) and those of healthy controls. We propose a hypothesis test that allows for this differentiation while taking advantage of the functional nature of the data. The methods represent the data using a common orthogonal basis expansion and reduce the dimension of the testing problem in a way that enables the application of traditional nonparametric univariate testing procedures. This results in a procedure that is not only computationally inexpensive but also allows for testing of higher order moments in functional principal component factor loadings.Simulation studies are presented to demonstrate the strength and validity of our approach. We also provide a comparison to a competing method. The proposed methodology is then illustrated by applying it to a state-of-the art diffusion tensor imaging (DTI) study where the objective is to compare white matter tract profiles in healthy individuals and multiple sclerosis (MS) patients.