报告地点：公司玉泉校区教三338
报告时间：2016年6月20日上午10：00-11：00
Title: Big Medical Data – Brain, Neurons and Risk Factors
Dr. Ruogu Fang
Assistant Professor
School of Computing and Information Sciences
Florida International University
Abstract:
Big data has made significant impacts in every aspect of our life. Medical and health fields have accumulated huge amount of data (with 500 petabytes in 2012 and 25 exabytes in 2020 expected). However, the explosive growth of digital health data does not mean the same increase of knowledge growth. In this talk, I will present the big picture of the challenges faced by the world and the US healthcare system in the age of big medical data, and opportunities open for research, and our advances on using the big medical data for more accurate and safer medical diagnosis. This talk will cover three research topics: brain, neurons and risk factors. With the ever-increasing amount of medical image and health informatics data (CT, MRI, PET, ultrasound, neuron, behavior risk factor surveys, etc.) in the hospitals and medical centers across the world, exploitation of the large-scale medical data would provide invaluable information for the medical image processing and analysis. The quality of medical image is a great challenge at low radiation dose and short acquisition time. Learning-based medical imaging is an inter-disciplinary field that bridges machine learning, computer vision, health informatics and medical imaging. It offers flexible and effective approaches to exploit the inherent structure of the massive medical image data.
报告人简介：
方若谷博士，现任美国佛罗里达国际大学计算与信息科学学院助理教授。方博士于2014年毕业于美国康奈尔大学电子与计算机工程学院，获博士学位；2009年毕业于公司竺可桢学院，获工程学士学位。方博士现任佛罗里达国际大学SMILE实验室的主任，研究领域包括医学大数据，智能医学影像，健康信息学，神经影像分析，计算机视觉，机器学习等。在国际知名刊物和国际会议发表论文30余篇, 包括IEEE Transaction on Medical Imaging(JCR一区，五年影响因子4.3), Medical Image Analysis (JCR一区，影响因子4.4) 以及MICCAI (医学图像顶级会议)。方博士获得美国国家科学基金CRII, Oak Ridge Associated Universities (ORAU) 青年教师奖，大脑图谱和治疗学学会青年科学教奖，IEEE国际图像处理大会(IEEE International Conference on Image Processing) 最佳论文奖, Medical Image Analysis（医学影像分析顶级期刊）最热门论文，Irwin and Joan Jacobs 学者奖学金。方博士担任国际稀疏算法和医学影像专题研究会联合主席，以及计算机医学影像和图像学期刊的客座主编。
方博士的SMILE(智能医学信息学习和评价实验室)研究医学大数据在大脑影像和脑部疾病的研究。研究领域包括智能化医学图像学习和分析、大脑动态学、神经细胞分析、风险因素预测等。这些研究领域旨在建立更安全、准确、快速的医学研究和医疗服务。欢迎访问SMILE Lab 的主页: http://smile.cs.fiu.edu
