讲座：Machine Learning in Medical Imaging
龚高浪老师课题组邀请了北卡罗来纳大学教堂山分校生物医学研究影像中心的石峰博士做学术报告，欢迎感兴趣的老师和同学参加。以下为报告信息：
报告时间:2月17日(本周三)下午2:00
报告地点:京师大厦9420会议室
报告人:石峰(北卡罗来纳大学教堂山分校)
报告题目: Machine Learning in Medical Imaging
报告摘要: Machine learning provides methods, techniques, and tools that can help solving diagnostic and prognostic problems in a variety of medical domains. In this talk, I will present our recent work of developing machine-learning algorithms in medical imaging computing applications. In the first part, I will introduce how to segment different brain tissues on first-year infant MR images by using random forest technique with multi-modality features. In the second part, I will demonstrate how to enhance image resolution of routine 3T MR images towards 7T image resolution and contrast by using paired dictionaries and sparse models. In the last part, I will talk about computer-aided prediction of autistic risk on 6-month infants by using multi-kernel SVM with features from brain white matter fiber tracts.
报告人简介: Dr. Shi received his Bachelor's Degree in electronics engineering from Peking University in 2002, and obtained his PhD in Computer Science from Institute of Automation, Chinese Academy of Sciences in 2008. He subsequently obtained postdoctoral training in Medical Image Computing at the University of North Carolina at Chapel Hill, where he has been a Research Assistant Professor of Radiology since 2011. He is also an affiliated faculty with the UNC Biomedical Research Imaging Center (BRIC). His research interests include pattern recognition and machine learning, multimodal medical image analysis, neuroanatomy and cognitive neuroscience, and statistical applications in neurodevelopment, neurological and psychiatric diseases.
