Generative models for medical image analysis
数学专题报告
报告题目(Title)：Generative models for medical image analysis
报告人(Speaker)：邱武 华中科技大学
地点(Place)：后主楼1220
时间(Time)：2024年11月19日(周二) 下午15：00-16：00
邀请人(Inviter)：段玉萍
报告摘要
Generative models can generate high-quality, realistic medical images from limited or noisy data sets. This capability not only aids in improving the quality and resolution of images but also facilitates the discovery of subtle patterns that might be missed by traditional analysis methods. Applications range from synthesizing new medical images to augment training data, to enhancing image reconstruction and segmentation processes. By integrating generative models into medical image analysis, we unlock new avenues for advancements in personalized medicine, ultimately aiming for better patient outcomes and more efficient clinical workflows.
主讲人简介
邱武，华中科技大学生命科学与技术学院、生物医学工程系教授，国家高层次青年人才、湖北省政府特殊津贴专家。曾任加拿大卡尔加里大学放射学系、临床神经医学系助理教授，加拿大Western University，Robarts Research Institute研究员。主要从事人工智能在医学影像分析中的应用研究，包括急性期脑卒中的影像学诊断，三维超声断层成像（UCT），多模影像导引前列腺穿刺与治疗等。在IEEE Trans. Medical Imaging， Medical Image Analysis，Radiology，Stroke，MICCAI等国际顶级期刊和会议上发表论文逾100篇。作为独立PI获得加拿大CIHR (Canadian Institutes of Health Research）以及Alberta Innovate多项经费支持。
