Abstract
The Fisher Information Matrix (FIM) plays a key role in the analysis and applications of statistical image recon-struction 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, which achieves a bias of less than 2% for mean sinogram values greater than 0.7. 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 reconstructed image resolution in both high and low count situations.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE Nuclear Science Symposium Conference Record |
| Editors | S.D. Metzler |
| Pages | 2012-2016 |
| Number of pages | 5 |
| Volume | 3 |
| State | Published - 2003 |
| Event | 2003 IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference - Portland, OR, United States Duration: Oct 19 2003 → Oct 25 2003 |
Other
| Other | 2003 IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference |
|---|---|
| Country | United States |
| City | Portland, OR |
| Period | 10/19/03 → 10/25/03 |
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Keywords
- Fisher Information Matrix
- Hyperparameters
- Uniform Resolution
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Industrial and Manufacturing Engineering
Cite this
Accurate estimation of the Fisher information matrix for the PET image reconstruction problem. / Li, Quanzheng; Asma, Evren; Qi, Jinyi; Bading, James R.; Leahy, Richard M.
IEEE Nuclear Science Symposium Conference Record. ed. / S.D. Metzler. Vol. 3 2003. p. 2012-2016 M5-3.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Accurate estimation of the Fisher information matrix for the PET image reconstruction problem
AU - Li, Quanzheng
AU - Asma, Evren
AU - Qi, Jinyi
AU - Bading, James R.
AU - Leahy, Richard M.
PY - 2003
Y1 - 2003
N2 - The Fisher Information Matrix (FIM) plays a key role in the analysis and applications of statistical image recon-struction 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, which achieves a bias of less than 2% for mean sinogram values greater than 0.7. 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 reconstructed image resolution in both high and low count situations.
AB - The Fisher Information Matrix (FIM) plays a key role in the analysis and applications of statistical image recon-struction 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, which achieves a bias of less than 2% for mean sinogram values greater than 0.7. 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 reconstructed image resolution in both high and low count situations.
KW - Fisher Information Matrix
KW - Hyperparameters
KW - Uniform Resolution
UR - http://www.scopus.com/inward/record.url?scp=11844282745&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11844282745&partnerID=8YFLogxK
M3 - Conference contribution
VL - 3
SP - 2012
EP - 2016
BT - IEEE Nuclear Science Symposium Conference Record
A2 - Metzler, S.D.
ER -