Image Reconstruction and Lesion Detection Using PET

Image Reconstruction and Lesion Detection Using PETQuanzheng Li
Research Associate, University of Southern CaliforniaHost: Krishna NayakAbstract:

Due to the tremendous success of the human genome project, human 
health care has emerged into an era of molecular and personal medicine, in
 which molecular imaging plays a key role. Among all the molecular imaging 
modalities, Positron Emission Tomography (PET) has a prominent position 
because of its flexibility and sensitivity. In this talk I will present our
 work on developing fast and accurate 3D and 4D image reconstruction methods
 for PET. After briefly summarize our work on static reconstruction, I will 
focus on dynamic reconstruction and introduce a fast globally convergent
fully 4D incremental gradient algorithm to estimate the continuous-time
 tracer density from list mode PET data. In the second part of the talk, I
 will describe a matched subspace detection method that uses the time
 activity curve (TAC) to distinguish tumors from background in dynamic FDG
PET, and then propose a Gaussian Random Filed (GRF) method with a given
 family wise error rate (FWER) to threshold the matched subspace detection
 statistic map. 

Biography:
Dr. Li is a Research Associate in Electrical Engineering at the University
 of Southern California. He received his BS from Zhejiang University, China
in 1997, his MS from Tsinghua University, China in 2000, and his PhD in 
Electrical Engineering from University of Southern California in 2005. His
 current research interests lie in applying signal and image processing
 theory to solve computational problems in molecular imaging.

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Alma Hernandez