Speaker

　　Title

　　Time

　　Venue

腾讯会议室 ID：667 937 947

腾讯直播间： https://meeting.tencent.com/l/NzgP0EmV5SJk

　　Abstract

Quantitative dual-energy CT (QDECT) has a potentially high degree of task-specific utility for medical, security, and other imaging applications. Accurate image reconstruction in QDECT remains a challenging task, largely because its data model is nonlinear. In recent years, progress has been made in developing optimization-based algorithms for accurate image reconstruction in QDECT. Because of the non-linear data in QDECT, the optimization problems devised are generally non-convex.  In the presentation, I will discuss the non-convex primal-dual (NCPD) algorithm that we have developed for image reconstruction through approximately solving a non-convex optimization problem in QDECT. Extensive numerical studies are carried out to verify that the NCPD algorithm can numerically accurately reconstruct images in QDECT.

If time allows, I would also discuss some of the claims in the literature that machine learning (ML), neural network (NN), deep learning (DL) or artificial intelligence (AI) can solve an inverse problem in CT. Specifically, I would share with the audience results of ML/NN/DL studies of colleagues around the world on a basic inverse problem in CT, which yield no evidence to support the claims at least for now.

　　Affiliation

Xiaochuan Pan is a Professor in the Department of Radiology, Department of Radiation & Cellular Oncology, the Committee on Medical Physics, the Comprehensive Cancer Center, and the College at The University of Chicago. His research centers on physics, algorithms, and engineering underpinning tomographic imaging and its biomedical and clinical applications. He has developed close clinical and industrial collaboration and established robust translational programs. He is the recipient of awards such as IEEE NPSS Early Achievement Award and IEEE EMBS Technical Award, a Fellow of AAPM, AIMBE, IAMBE, IEEE, OSA, and SPIE, and Distinguished Investigator Award of ARR. Dr. Pan has served as a chair and/or reviewer of study sections/review panels for funding agencies, including NIH, NSF, DOE, NSERC, NSFC, and ASF. He is the Editor-in-Chief of IEEE Trans. Biomed Eng.,  and has served or is serving as an associate editor (or editorial board member) for journals in the field such as IEEE Trans. Med. Imaging, IEEE Trans. Biomed Eng., IEEE J. Transl. Eng. Health and Med., Phys. Biol. Med., Med. Phys., and J. Med. Imaging, as a chair/member of technical committees of professional organizations such as IEEE, RSNA, and AAPM, and as a general chair, chair/member of programs, themes, and  technical/scientific committees for conferences such as IEEE EMBC, IEEE MIC, RSNA, AAPM, and MICCAI.