Paper Info
Title
Accurate estimation of the Fisher information matrix for the PET image reconstruction problem.
Abstract
The Fisher information matrix (FIM) plays a key role in the analysis and applications of statistical image reconstruction methods based on Poisson data models. The elements of the FIM are a function of the reciprocal of the mean values of sinogram elements. Conventional plug-in FIM estimation methods do not work well at low counts, where the FIM estimate is highly sensitive to the reciprocal mean estimates at individual detector pairs. A generalized error look-up table (GELT) method is developed to estimate the reciprocal of the mean of the sinogram data. This approach is also extended to randoms precorrected data. Based on these techniques, an accurate FIM estimate is obtained for both Poisson and randoms precorrected data. As an application, the new GELT method is used to improve resolution uniformity and achieve near-uniform image resolution in low count situations.
Year
DOI
Venue
2004
10.1109/TMI.2004.833202
IEEE Transactions on Medical Imaging
Keywords
DocType
Volume
fisher information matrix estimation method,near-uniform image resolution,uniform resolution.,resolution uniformity,generalized error look-up table method,poisson data models,randoms precorrected data,statistical analysis,image resolution,pet image reconstruction,poisson distribution,pet image reconstruction problem,index terms—fisher information matrix,statistical image reconstruction methods,image reconstruction,sinogram,positron emission tomography,pet,fisher information matrix,medical image processing,reciprocal mean estimates,indexing terms,look up table,data model,generalization error
Journal
23
Issue
ISSN
ISBN
9
0278-0062
0-7803-8257-9
Citations 
PageRank 
References 
14
1.50
9
Authors
5
Name
Order
Citations
PageRank
Quanzheng Li118132.36
Evren Asma2728.01
Jinyi Qi328435.82
James R Bading4141.50
Richard M Leahy51768295.29