888.3net新浦京游戏机器人与信息自动化研究所 天津市智能机器人技术重点实验室

Institute of Robotics and Automatic Information System

Tianjin Key Laboratory of Intelligent Robotics

2023年春季先进机器人与人工智能系列学术讲座（第229期）

Seminar Series：Advanced Robotics & Artificial Intelligence

报告时间：2023年6月10日（周六）14:30-16:00

报告地点：线上，腾讯会议：474-105-506，会议密码：123123

报告嘉宾：Lei Li 牛津大学博士后

报告题目：Artificial Intelligence in Cardiac Image Computing and Modeling

报告摘要：

Cardiac imaging plays a key role in the management of patients with cardiovascular diseases. Fully automated computing and modelling of cardiac images could be beneficial for clinical research and evidence-based patient management. Deep learning (DL) is widely used in cardiac image analysis, but sometimes DL-based models might fail due to the limited understanding of the data and task. It is essential to deeply understand the data and tasks we have for developing robust models. In this talk, Dr. Lei Li will mainly employ the left atrial LGE MRI computing work as an example, to introduce how to design a specific DL-based model based on the characteristics of the task and data. Additionally, she will also introduce her recent works in multi-modality image computing and cardiac digital twins. The involved techniques in cardiac image analysis, such as image segmentation and registration, multi-modality data integration, multi-center data processing, as well as cardiac simulation and modelling, can be easily extended for other medical image analysis task for precision medicine.

报告人简介：

Dr Lei Li is a Postdoctoral Research Assistant at the Institute of Biomedical Engineering, University of Oxford. She obtained her PhD degree from the School of Biomedical Engineering, Shanghai Jiao Tong University in 2021. During her PhD, she was a visiting PhD student at Fudan University and King’s College London, respectively. She obtained the SJTU 2021 Outstanding Doctoral Graduate Development Scholarship. Her research interest is at the interface between machine learning and medical imaging, including developing novel computational methods for medical image analysis as well as translating the methods to clinical research and healthcare. She has already published more than 30 papers with 800+ citations, incl. 6 first/ corresponding authored articles accepted in peer-reviewed journals and 7 first-authored international conference papers. Some of these works have been selected as the most popular and most cited paper in MedIA and IEEE TMI. She is now the Board Member of Women in MICCAI (WiM) and the Editorial Board Member of the Journal of Medical Artificial Intelligence. She has co-organizered four MICCAI challenge events, incl. LAScarQS 2022, MyoPS 2020, MS-CMRSeg 2019, and MM-WHS 2017. She is a reviewer for many journals and conferences, incl. MedIA, IEEE TPAMI, IEEE TMI, IEEE TBME, Neurocomputing, IPMI, ISBI, MIDL, and MICCAI.