Speaker：Dinggang Shen (Professor, Department of Radiology, University of North Carolina at Chapel Hill)
Time：9:30 am,July 9 (Saturday), 2011
Venue：Conference Room of Optical Image Analysis and Learning Center (OPTIMAL)
Speaker Profile：
This talk will summarize our work on analysis of MR brain images. Our main goal is to develop automated analysis methods for precise quantification of subtle and complex structural/functional changes in the brains, with applications in early detection of brain disorders, such as Alzheimer's Disease (AD). To achieve this goal, we developed a 3D brain registration method, called HAMMER, for inter-subject registration, and also a 4D (3 spatial dimensions + 1 temporal dimension) brain registration method to obtain more accurate measurements for tiny longitudinal brain changes, compared to the 3D registration methods. For better alignment of a population of images, we have recently developed several group-wise registration methods for joint registration of all images together, thus further improving the registration accuracy among all images. With accurate brain structural/functional information measured by our registration methods, we further developed a multivariate analysis method, based on support vector machine, to jointly consider all structural/functional changes for determining the group difference between normal and abnormal brains, i.e., due to diseases, aging, or brain disorders. We have applied our developed methods to computer-aided diagnosis of schizophrenia and AD. Details of these 3D, 4D, and group-wise registration methods, as well as brain classification methods, will be discussed in this talk.
Summary：
Dinggang Shen is a (tenured) Professor of Radiology, Biomedical Research Imaging Center (BRIC), Computer Science, and Biomedical Engineering in the University of North Carolina at Chapel Hill (UNC-CH). He is currently directing the Image Display, Enhancement, and Analysis (IDEA) Lab in the Department of Radiology, and also the medical image analysis core in the BRIC. Before joining UNC-CH, he was a tenure-track assistant professor in the University of Pennsylvanian (UPenn), and a faculty member in the Johns Hopkins University. Dr. Shen’s research interests include medical image analysis, computer vision, and pattern recognition. He has published more than 300 papers in the international journals and conference proceedings. He serves as an editorial board member for five international journals.
Time：9:30 am,July 9 (Saturday), 2011
Venue：Conference Room of Optical Image Analysis and Learning Center (OPTIMAL)
Speaker Profile：
This talk will summarize our work on analysis of MR brain images. Our main goal is to develop automated analysis methods for precise quantification of subtle and complex structural/functional changes in the brains, with applications in early detection of brain disorders, such as Alzheimer's Disease (AD). To achieve this goal, we developed a 3D brain registration method, called HAMMER, for inter-subject registration, and also a 4D (3 spatial dimensions + 1 temporal dimension) brain registration method to obtain more accurate measurements for tiny longitudinal brain changes, compared to the 3D registration methods. For better alignment of a population of images, we have recently developed several group-wise registration methods for joint registration of all images together, thus further improving the registration accuracy among all images. With accurate brain structural/functional information measured by our registration methods, we further developed a multivariate analysis method, based on support vector machine, to jointly consider all structural/functional changes for determining the group difference between normal and abnormal brains, i.e., due to diseases, aging, or brain disorders. We have applied our developed methods to computer-aided diagnosis of schizophrenia and AD. Details of these 3D, 4D, and group-wise registration methods, as well as brain classification methods, will be discussed in this talk.
Summary：
Dinggang Shen is a (tenured) Professor of Radiology, Biomedical Research Imaging Center (BRIC), Computer Science, and Biomedical Engineering in the University of North Carolina at Chapel Hill (UNC-CH). He is currently directing the Image Display, Enhancement, and Analysis (IDEA) Lab in the Department of Radiology, and also the medical image analysis core in the BRIC. Before joining UNC-CH, he was a tenure-track assistant professor in the University of Pennsylvanian (UPenn), and a faculty member in the Johns Hopkins University. Dr. Shen’s research interests include medical image analysis, computer vision, and pattern recognition. He has published more than 300 papers in the international journals and conference proceedings. He serves as an editorial board member for five international journals.
