Accurate estimation of the Fisher information matrix for the PET image reconstruction problem

Quanzheng Li, Evren Asma, Jinyi Qi, James R. Bading, Richard M. Leahy

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1057-1064
Number of pages8
JournalIEEE Transactions on Medical Imaging
Issue number9
StatePublished - Sep 2004


  • Fisher information matrix
  • Image reconstruction
  • PET
  • Uniform resolution

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics


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