Machine Learning in Neuroimaging Analysis
内容：This talk will mainly discuss some of our recently accepted MICCAI 2017 papers, using deep learning for various neuroimaging applications. Specifically, 1) in neuroimaging analysis, we have developed an automatic brain measurement method for the first-year brain images with the goal of early detection of autism such as before 1 year old. This effort is aligned with our recently awarded Baby Connectome Project (BCP) (where I serve as Co-PI), which will acquire MR images and behavioral assessments from typically developing children, from birth to five years of age. Besides, we have also developed a novel landmark-based deep learning method for early diagnosis of Alzheimer’s Disease (AD) with the goal of potential early treatment. 2) In image synthesis, we have developed a cascaded 3D CNN for reconstructing 7T-like MRI from 3T MRI for simultaneously enhancing image quality and tissue segmentation. Also, we have developed a novel Generative Adversarial Networks (GAN) based method to estimate CT from MRI, for helping MRI-based cancer radiotherapy. All these techniques will be introduced in this talk.
沈定刚教授是我国“千人计划”入选者，美国北卡罗来纳大学教堂山分校终身教授。主要从事医学图像分析、计算机视觉、模式识别等领域的研究。作为课题负责人，获得过十余项美国研究基金。其提出的大脑弹性配准算法HAMMER是该领域的知名算法，2006年获得IEEE Signal Processing Society年度最佳论文，被引用700多次，相关软件下载10000多次。在Human Brain Mapping、 IEEE Trans. on Pattern Analysis and Machine Intelligence等国际学术期刊和会议发表700多篇论文。担任六个国际期刊的编委，是医学图像计算和计算机辅助治疗组织(MICCAI)的执委会成员，美国医学和生物工程学会(AIMBE) Fellow。
Dinggang Shen is a 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 Center for Image Analysis and Informatics, the Image Display, Enhancement, and Analysis (IDEA) Lab in the Department of Radiology, and also the medical image analysis core in the BRIC. 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 700 papers in the international journals and conference proceedings. He serves as an editorial board member for six international journals. He has also served in the Board of Directors, The Medical Image Computing and Computer Assisted Intervention (MICCAI) Society, in 2011-2015. Dr. Shen is Fellow of AIMBE.