TITLE: Quantitative 3D Brain Structure Analysis of Subtypes of Autism by Non-Invasive Magnetic Resonance Imaging

ABSTRACT:
With vast quantities of medical images routinely collected by continually improving medical imaging hardware and technologies, the data analysis task would be impractically time-consuming and laborious if performed manually. Consequently, powerful computer-based processing and analysis algorithms are in great demand. In this talk, I will talk about our recent work on semi-automatic/automatic 2D/3D image segmentation and 2D/3D shape analysis, as well as their applications in quantitative MRI-based 3D brain structure analysis for autism research.

Autism is a complex neurodevelopmental disorder of childhood, currently affecting 1 in 166 children. It is defined by the presence of social deficits, abnormalities in communication, the presence of stereotyped, repetitive behaviors, and a characteristic course. While the neuroanatomical basis of this condition is not yet known, numerous lines of evidence suggest abnormalities in brain structure and brain connectivity may be characteristic of autism.

We have been working with Dr. Judith Miles and her colleagues at the Thompson Center for Autism and Neurodevelopmental Disorders at the University of Missouri at Columbia to extract 3D geometric shape of important brain from Magnetic Resonance Imaging datasets and compare them with normal brain counterparts. The identification of specific and consistent regions of brain structure abnormality in children with autism by MRI, may lead not only to earlier and more reliable diagnosis, but also to an increased understanding of causal factors involved in autism and an effective biological intervention or even prevention of infantile autism.

BIO:
Ye Duan is an Associate Professor of Computer Science at University of Missouri-Columbia.  He received his B.A. degree in Mathematics from Peking University in 1991. He received his M.S. degree in Mathematics from Utah State University in 1996. He received his M.S. and Ph.D. degree in Computer Science from the State University of New York at Stony Brook in 1998 and 2003. From September 2003 to August 2009, he was an Assistant Professor of Computer Science at University of Missouri-Columbia. His research interests are Computer Graphics, Shape Modeling, Biomedical Imaging, Computer Vision, and Virtual Reality.