模式识别系列讲座

Lecture Series in Pattern Recognition

题    目（TITLE）：  Smoothing Imaging Data in Population Studies

讲 座 人（SPEAKER）:  Dr. Hongtu Zhu；Department of Biostatistics and Biomedical Research Imaging Center, UNC-Chapel Hill

主 持 人 (CHAIR)： Prof. Yong Fan

时    间 (TIME)：  9:30AM, June24 (Friday)

地    点 (VENUE)： The Second Meeting Room, 13th Floor

报告摘要（ABSTRACT）：

Motivated by recent work studying massive imaging data in large neuroimaging studies, we propose various multiscale adaptive smoothing models (MASM) for spatially modeling the relation between high-dimensional imaging measures on a three-dimensional (3D) volume or a 2D surface with a set of covariates. MASM can be used to carry out population studies and imaging denoising.

MASM is a novel generalization of propagation-seperation algorithm, local smoothing methods, and statistical modelling. We develop novel estimation procedures for MARMs and systematically study their theoretical properties. We conduct Monte Carlo simulation and real data analyses, such as ADNI and twin study, to examine the fi nite-sample performance of the proposed procedures.

报告人简介（BIOGRAPHY）：

Dr. Hongtu Zhu is an associate professor of biostatistics in the department of biostatistics and Biomedical Research Imaging Center at the UNC-CH. He received his Ph. D. from the Chinese University of Hong Kong in 2000.  He is a fellow of American Statistical Association and Institute of Mathematical Statistics. His current researches of interest include missing data problems, model diagnostics,  stochastic optimization algorithm,  imaging denoising, diffusion tensor imaging, functional imaging analysis, imaging genetics, and data mining.