Title: Computational Anatomy: Quantitative Study of Neuroanatomy with Diffeomorphisms
Speaker: Xiaoying Tang, Ph.D., Assistant Professor, Sun Yat-sen University Carnegie Mellon University (SYSU-CMU) Joint Institute of Engineering, SYSU
Location: Jingshi Building, Room 9420
Time: 10:00 AM, April 11, 2016
Abstract: Computational Anatomy (CA) is an emerging discipline that aims to understand neuroanatomy by utilizing a comprehensive set of mathematical tools from Riemannian geometry alongside a “textbook” composed of MR images from a variety of modalities. Central to CA is the formulation of correspondences between different coordinate systems. In this talk, I will introduce the basics of CA before presenting a sophisticated algorithm for the creation of such spatial correspondences between anatomical systems. With this established, I will cover two main practical applications of CA in the quantitative study of neuroanatomy. The first one concerns how we can create a hierarchical structure identification system for the human brain and I will introduce an original pipeline designed for brain parcellation using T1-weighted images and diffusion tensor images. The second application will focus on parcellation and shape based neuroinformatics of the brain's anatomy along with their relevance to the diagnosis and prognosis of various neurodegenerative disorders. Results from numerous clinical datasets will be presented.
About the speaker: Xiaoying Tang, Ph.D., Assistant Professor at the SYSU-CMU Joint Institute of Engineering, SYSU, is also jointly appointed as an Associate Professor at the School of Electronics and Information Technology, SYSU and holds the Adjunct Professorship at the Electrical and Computer Engineering (ECE) Department of Carnegie Mellon University and the ECE Department of Johns Hopkins University. Dr. Tang obtained her Ph.D. degree from Johns Hopkins University in 2014 and her research focuses upon mathematical medical image analysis, brain segmentation and registration, multi-modality MRI analysis, statistical shape analysis, machine learning, and neuroinformatics. Dr. Tang is an associate editor of
the Journal of Alzheimer’s Disease as well as the guest associate editor of
Frontier in Neuroscience and
Frontiers in Neurology.
