Paper Info
Title
Direct parametric image reconstruction of rapid multi-tracer PET.
Abstract
The separation of multiple PET tracers within an overlapped scan based on intrinsic difference of pharmacokinetics is challenging due to the limited SNR of PET measurements and high complexity of fitting models. This study developed a novel direct parametric reconstruction method by integrating a multi-tracer model with reduced number of fitting parameters into image reconstruction. To incorporate the multitracer model, we adopted EM surrogate functions for the optimization of the penalized log-likelihood. The algorithm was validated on realistic simulation phantoms and real rapid [F-18]FDG and [F-18]FLT PET imaging of mice with lymphoma mouse tumor. Both results have been compared with conventional methods and demonstrated evident improvements for the separation of multiple tracers.
Year
DOI
Venue
2013
10.1007/978-3-642-40760-4_20
Lecture Notes in Computer Science
Field
DocType
Volume
Iterative reconstruction,Computer vision,TRACER,Parametric Image,Pattern recognition,Computer science,Arterial input function,Parametric statistics,Artificial intelligence
Conference
8151
Issue
ISSN
Citations 
Pt 3
0302-9743
2
PageRank 
References 
Authors
0.41
3
4
Name
Order
Citations
PageRank
Xiaoyin Cheng120.75
Nassir Navab26594578.60
Sibylle Ilse Ziegler3887.62
Kuangyu Shi4368.12