Direct Estimation From List-Mode Data For Reversible Tracers Using Graphical Modeling
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)(2015)
摘要
We propose a novel method to directly estimate parametric images from listmode PET data for reversible tracers based on an inhomogeneous Poisson process model. We use a relative equilibrium graphical model, similar to the Logan plot, to linearize the problem. A static sinogram from time of tracer injection to the steady state is incorporated to improve the ill-conditioning of the estimation problem. Cramer-Rao analysis and Monte-Carlo simulation demonstrate that our method improves the conditioning of the estimation problem and provides higher contrast recovery and smaller standard deviation compared with a sinogram based direct estimation approach.
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关键词
reversible tracers,parametric image estimation,list-mode PET data,inhomogeneous Poisson process model,relative equilibrium graphical model,Cramer-Rao analysis,Monte-Carlo simulation,sinogram based direct estimation approach
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