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活动类型：学术报告

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题   目：Computational Methods for Quantitative Analysis of Brain Diseases
报告人：Dinggang Shen（北卡大学副教授）
时   间：7月21日（本周二）下午3点
地   点：浙江大学数学中心201室

Professor Dinggang Shen主要从事计算神经影像学，今年已经在PNAS，Neuroimage，Neurology上发了4篇文章。

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 more than 8,000 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. In addition, 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. Some new applications, i.e., in early brain development from two weeks to 1 year old and 2 year old, will be also presented.