报告题目： Infant Brain MRI Analysis
报 告 人：美国北卡罗来纳大学教堂山分校 助理教授 王利
报告时间：2019年10月19日（周六）上午09：00—10：00
报告地点：12教703
报告人简介：
王利，男，博士，助理教授，现任职于美国北卡罗来纳大学教堂山分校，IEEE Senior Member。2010年毕业于南京理工大学计算机科学与技术学院，获博士学位。多年来一直致力于研究婴幼儿大脑早期发育，包括图像分割，重建，早期自闭症诊断，以课题负责人身份分别获得美国国立卫生研究院NIH Career Award和NIH R01项目资助。在IEEE Transactions on Medical Imaging，Medical Image Analysis, Human Brain Mapping, NeuroImage, Cerebral Cortex, Medical Physics, PNAS等发表学术论文80余篇，Google Scholar总引用4500次，h-index=34。2010年分别获得Computerized Medical Imaging and Graphics和Signal Processing论文高引奖；2015年获得Medical Physics最佳论文奖(Editor's Choice & Cover page); 2014和2018年获得NeuroImage论文高引奖。多次在MICCAI Challenge获得第一名，并成功组织2次MICCAI Challenge：iSeg-2017和iSeg-2019。目前在多个国际期刊担任编委。
报告内容简介：
Recent progress in infant MRI technology allows us to track the dynamic brain developmental trajectories in vivo during the first year of life, which can greatly increase our very limited knowledge on normal early brain development, and also provide important insights into early neurodevelopmental disorders, such as autism spectrum disorder and schizophrenia. However, the existing neuroimaging computational tools, which were mainly developed for older children and adult brains, are ill-suited for infant brain studies, due to great challenges in tissue segmentation and labeling, caused by the extremely low contrast, insufficient resolution, severe partial volume effects, and dynamic growth. In this presentation, Dr. Wang will introduce learning-based methods for infant brain images analysis, including tissue segmentation of cerebrum and cerebellum, hippocampal subfield, and imaging-biomarkers for early diagnosis of autism.
