Accelerated direct reconstruction of PET parametric images using augmented Lagrangian optimization

Guobao Wang, Jinyi Qi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Direct estimation of physiologically or biochemically important parameters from raw projection data is challenging in dynamic positron emission tomography (PET) due to the coupling between tomographic image reconstruction and nonlinear kinetic parameter estimation. Optimization transfer algorithms have been previously developed to solve the complex optimization problem. These algorithms, however, can suffer from slow convergence rate. This paper proposes an accelerated iterative algorithm for direct reconstruction of kinetic parameters through variable splitting under the framework of augmented Lagrangian optimization. Similar to the optimization transfer algorithms, the proposed algorithm splits each iteration of direct reconstruction into two separate steps: dynamic image reconstruction and pixel-wise nonlinear least squares kinetic fitting. The unique advantage of the new algorithm is its flexibility to employ any existing reconstruction algorithms in the reconstruction step, which can substantially accelerate the convergence speed. Computer simulations show that the proposed direct algorithm can be efficiently implemented and achieve much faster convergence speed than the optimization transfer algorithm.

Original languageEnglish (US)
Title of host publicationProceedings - International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781479923748
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015


Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States


  • Dynamic PET
  • image reconstruction
  • optimization algorithm
  • parametric imaging

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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