You cannot register for this webinar

The liver, being the largest solid organ in the human body, plays a pivotal role in numerous physiological processes. It is also a frequent site for tumors and chronic diseases. Early detection and precise diagnosis of liver conditions are essential for enhancing patient outcomes, with computed tomography (CT) serving as a widely utilized imaging tool. In this presentation, we will discuss our work on screening, diagnosing, and staging liver tumors and chronic diseases using CT, particularly non-contrast CT, which is both cost-effective and highly accessible. Speaker: Ke Yan is a Staff Algorithm Expert in the Alibaba DAMO Academy. He obtained his PhD degree from the Department of Electronic Engineering, Tsinghua University. Then, he worked as a postdoctoral fellow in the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institute of Health, US. His research mainly focuses on medical image analysis, especially on disease screening and diagnosis in CT images using deep learning. He published the DeepLesion dataset, a large-scale and universal CT lesion dataset. He also won the RSNA Trainee Research Prize in 2018 and Tsinghua University Excellent Doctoral Dissertation Award in 2016. He has published papers and abstracts on IEEE Transactions on Medical Imaging, Radiology: Artificial Intelligence, npj Digital Medicine, CVPR, MICCAI, RSNA, etc., and got 4200 citations. He also holds 6 granted patents in the US and 12 in China.