DocumentCode
2522806
Title
VARIANCE APPROXIMATION FOR EXPONENTIAL FAMILY PENALIZED MAXIMUM LIKELIHOOD ESTIMATORS: APPLICATION TO KINETIC PARAMETRIC ESTIMATION
Author
Li, Quanzheng ; Leahy, Richard M.
Author_Institution
Signal & Image Process. Inst., Southern Carolina Univ., Los Angeles, CA
fYear
2007
fDate
12-15 April 2007
Firstpage
916
Lastpage
919
Abstract
We further simplify previously published general approximate expressions for the covariance of penalized maximum likelihood estimators for likelihoods with the canonical form of the exponential family. The resulting expression makes calculation of the covariance more tractable for cases involving complicated log-likelihood expressions. We use this approximation to derive the covariance of direct estimates of voxel-wise kinetic parameters from list mode and bin mode PET data. To evaluate the accuracy of the approximation we simulate a simple parametric image reconstruction problem and demonstrate that the approximate covariances match well with the empirical covariances.
Keywords
covariance analysis; image reconstruction; maximum likelihood estimation; medical image processing; positron emission tomography; PET; covariance; image reconstruction; kinetic parametric estimation; maximum likelihood estimators; variance approximation; Equations; Image processing; Image reconstruction; In vivo; Kinetic theory; Maximum likelihood estimation; Molecular imaging; Parameter estimation; Positron emission tomography; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
Conference_Location
Arlington, VA
Print_ISBN
1-4244-0672-2
Electronic_ISBN
1-4244-0672-2
Type
conf
DOI
10.1109/ISBI.2007.357002
Filename
4193436
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