报告人：刘九龙副研究员

报告题目：Image Reconstruction Using Shape Prior, Statistical Prior, and Beyond

摘要：As the advances in imaging modalities in which the image reconstruction problems are mathematically inverse problems, many new kinds of inverse problems have emerged and trends to being high dimensional but with low-cost data acquisition. In order to efficiently and stably solve the under-determined and ill-conditioned inverse problems in high-dimensional medical imaging and compressed sensing, we established accurate statistical models for data fitting and images priors such as shape priors, statistical priors by generative models. In this presentation, I will introduce some of these methods and our recent results for image reconstruction, such as joint image reconstruction and indirect registration, phase retrieval and some other nonlinear inverse problems.

报告时间：2022年7月13日周三上午10:00-12:00

报告形式：腾讯会议937672481

报告人简介：刘九龙，中国科学院数学与系统科学研究院计算数学与科学工程计算研究所副研究员。于2017年获得上海交通大学数学博士学位，2018年至2021年在新加坡国立大学数学系从事博士后研究。主要研究方向包括变分方法、优化算法和机器学习理论以及探索它们在医学图像重建和数据处理中的应用。他在SIAM Journal on Imaging Sciences、Inverse Problems、IEEE Transactions on Medical Imaging等杂志以及ICLR、CVPR、MICCAI等机器学习会议上发表了十多篇相关研究的论文。