CAIR Medtech Seminar #7 AI in Medical Image Analysis: Challenges and Solutions
活动日期: 2023年10月6日
Below are the talk details:
Dr. Yixuan Yuan, Assistant Professor in Dept. of Electronic Engineering, Chinese University of Hong Kong
Talk title: AI in Medical Image Analysis: Challenges and Solutions
Abstract: The success of deep learning in many pattern recognition applications has brought excitement and high expectations that artificial intelligence can bring revolutionary changes in healthcare. The potential of applying deep learning to medical image analysis provides decision support for clinicians and improves the accuracy and efficiency of various diagnostic as well as treatment processes. Despite its breakthroughs, the application in clinical practice still suffers from several challenges, such as data imperfection, data heterogeneity, data privacy, and lack of model transparency. In this talk, I will share our recent progress in developing deep learning methods by addressing these challenges for medical image analysis, with application to disease diagnosis, lesion detection, and segmentation.
Biography: Yixuan Yuan is an assistant professor in the Department of Electronic Engineering, Chinese University of Hong Kong. Her research interest is AI in healthcare to promote precision medicine, especially for medical image diagnosis, abnormality detection, and segmentation. She was an Assistant Professor in the Department of Electrical Engineering, City University of Hong Kong during 2018-2022 and she was a postdoctoral fellow in the Department of Radiation Oncology, Stanford Cancer Center, Stanford University during 2017-2018. She received the Ph.D. degree in Electronic Engineering from the Chinese University of Hong Kong (CUHK) in 2016 with Hong Kong Postgraduate Fellowship (HKPFS), the B.S. degree in Automation from Northwestern Polytechnical University (NPU) with honor in 2010. She received several premium awards including the CVPR 2022 Best Paper Finalist, MICCAI 2022 Young Scientist Award (supervisor), Outstanding Teacher Award 2018/19 in CityU EE, 2017 Young Scientist Award in Engineering by Hong Kong Institute of Science, Best Paper Award in ICMA 2013, School of Medicine Dean’s Postdoctoral Fellowship at Stanford University.