报告摘要：

Positron emission tomography is a molecular imaging modality widely used in oncology, neurology, and cardiology. In this talk, I will describe a new framework that we recently developed for PET image reconstruction, namely the kernel-based image reconstruction. The kernel-based framework allows easy incorporation of prior or side information into PET image reconstruction through a kernel matrix. The reconstruction algorithm is easy to implement. Applications of the kernel-based reconstruction to dynamic PET and multimodal image reconstruction will be shown.  
 
报告人简介：

Jinyi Qi is a Professor in the Department of Biomedical Engineering at University of California, Davis. He received his Ph.D. degree in Electrical Engineering from the University of Southern California in 1998. He is a fellow of the American Institute for Medical and Biological Engineering (AIMBE) and IEEE. He has served as an Associate Editor of the IEEE Transactions of Medical Imaging since 2006. His research interests include statistical image reconstruction, medical image processing, image quality evaluation, and imaging system optimization.