Name
Title | ||
|---|---|---|
Analysis of penalized likelihood image reconstruction for dynamic PET quantification. |
Abstract | ||
|---|---|---|
Quantification of tracer kinetics using dynamic positron emission tomography (PET) provides important information for understanding the physiological and biochemical processes in humans and animals. A common procedure is to reconstruct a sequence of dynamic images first, and then apply kinetic analysis to the time activity curve of a region of interest derived from the reconstructed images. Obviously, the choice of image reconstruction method and its parameters affect the accuracy of the time activity curve and hence the estimated kinetic parameters. This paper analyzes the effects of penalized likelihood image reconstruction on tracer kinetic parameter estimation. Approximate theoretical expressions are derived to study the bias, variance, and ensemble mean squared error of the estimated kinetic parameters. Computer simulations show that these formulae predict correctly the changes of these statistics as functions of the regularization parameter. It is found that the choice of the regularization parameter has a significant impact on kinetic parameter estimation, indicating proper selection of image reconstruction parameters is important for dynamic PET. A practical method has been developed to use the theoretical formulae to guide the selection of the regularization parameter in dynamic PET image reconstruction. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TMI.2008.2008971 | IEEE Trans. Med. Imaging |
Keywords | Field | DocType |
penalized likelihood image reconstruction,time activity curve,maximum likelihood estimation,tracer kinetic parameter estimation,tracers,noise analysis,biochemistry,penalized maximum likelihood,image reconstruction,physiological processes,tracer kinetic modeling,positron emission tomography,biochemical processes,medical image processing,region of interest,kinetic analysis,image analysis,parameter estimation,kinetic theory,monte carlo method,computer simulation,kinetics,algorithms | Iterative reconstruction,Computer vision,Monte Carlo method,Expression (mathematics),Mean squared error,Regularization (mathematics),Artificial intelligence,Estimation theory,Region of interest,Mathematics,Time Activity Curve | Journal |
Volume | Issue | ISSN |
28 | 4 | 1558-254X |
Citations | PageRank | References |
3 | 0.53 | 19 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guobao Wang | 1 | 86 | 12.68 |
| Jinyi Qi | 2 | 284 | 35.82 |