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EECS Distinguished Seminar Series
Computational Methods for Quantitative Analysis of Brain Diseases
Dr. Dinggang Shen
Thursday, June 28, 2007
3:00PM ~ 4:00PM, Harris Center 101
Abstract
This talk will summarize our work on analysis of MR brain images. Our main research goal is to develop automated image analysis methods for precisely quantifying subtle and complex structural/ functional changes in the brains, to be used for early detection of brain diseases, such as Alzheimer's Disease (AD). Accordingly, we developed a 3D brain registration method, called HAMMER, which has been successfully applied to many large clinical research studies and clinical trials involving ~5,000 MR brain images. In order to measure the tiny longitudinal brain changes, i.e., due to AD, we also have developed a 4D (3 spatial dimensions + 1 temporal dimension) brain registration algorithm and obtained more accurate measurement results, compared to those by 3D registration algorithm. Moreover, we have developed multivariate analysis methods, based on support vector machine, to jointly consider all structural/functional changes for determining the group difference between brains, due to diseases, aging, or development. This method has been used for classifying schizophrenia patients from normal controls, and for lie detection based on the functional MR images. Details of these 3D and 4D registration algorithms and nonlinear brain analysis methods will be discussed in this talk.
Short Bio
Dinggang Shen received all of his degrees from Shanghai JiaoTong University. He is an assistant professor (tenure-track) in the Department of Radiology at University of Pennsylvania (Upenn) since July 2002. Before moving to Upenn, he was a faculty member in Johns Hopkins University. Dr. Shen is on the Editorial Board of Pattern Recognition, International Journal of Image and Graphics, and International Journal for Computation Vision and Biomechanics. He also served as a reviewer for numerous international journals and conferences, as well as NIH, NSF and other grant foundations. He has published over 160 articles in journals and proceedings of international conferences. His research interests include medical image analysis, pattern recognition, and computer vision.
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