[特邀报告]Pushing the limitation of PET imaging - 报告详情

Pushing the limitation of PET imaging
编号:44 访问权限:仅限参会人 更新:2021-11-05 16:51:09 浏览:125次 特邀报告

报告开始:2021年11月13日 13:55 (Asia/Shanghai)

报告时间:25min

所在会议:[PS1] Plenary Session 1 [AI1] Workshop on AI

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摘要
PET has been widely used for imaging 2D or 3D tomography of radioisotope distribution within the patient. But due to the high level noise of the measurement, accurate estimation of isotope distribution is still a challenging issue. During the early development of PET, researches developed the filtered back-projection (FBP) model based on Radon transform for reconstructing PET images. On the other hand, assuming data is Poisson distributed, iterative statistical reconstruction algorithms are able to model the physical detection process, and thus have been the primary focus of many recent efforts. However, from the perspective of statistical inference, such high dimensional maximum likelihood estimators are inevitably ill-conditioning. In this talk, I will discuss the limitation of PET, and the possible solutions.
关键字
报告人
Huafeng Liu
Professor Zhejiang University

Professor, Zhejiang University
* Director of the Hamamatsu-ZJU joint photonics Laboratory, Zhejiang University

Prof. Huafeng Liu received his B.S. in Optical Engineering, M.S. in Measurement Techniques and Instruments, and Ph.D. in Positron Emission Tomography in 2001, all from the Department of Optical Engineering, Zhejiang University. From 2001 to 2003, he was a postdoctoral fellow at Hong Kong University of Science and Technology, working on statistical filtering and inverse mechanics strategies for cardiac image analysis and PET image reconstruction. He is currently a full professor at Zhejiang University. 

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重要日期

摘要提交日期:

2021/08/31

2021/10/25

全文投稿日期:  

2021/09/15

2021/10/25

录取通知日期: 

2021/09/30

2021/11/01

会议日期:   2021-11-12-2021-11-14

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