A residual correction method for high-resolution PET reconstruction with application to on-the-fly Monte Carlo based model of positron range

Lin Fu, Jinyi Qi

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Purpose: The quality of tomographic images is directly affected by the system model being used in image reconstruction. An accurate system matrix is desirable for high-resolution image reconstruction, but it often leads to high computation cost. In this work the authors present a maximum a posteriori reconstruction algorithm with residual correction to alleviate the tradeoff between the model accuracy and the computation efficiency in image reconstruction. Methods: Unlike conventional iterative methods that assume that the system matrix is accurate, the proposed method reconstructs an image with a simplified system matrix and then removes the reconstruction artifacts through residual correction. Since the time-consuming forward and back projection operations using the accurate system matrix are not required in every iteration, image reconstruction time can be greatly reduced. Results: The authors apply the new algorithm to high-resolution positron emission tomography reconstruction with an on-the-fly Monte Carlo (MC) based positron range model. Computer simulations show that the new method is an order of magnitude faster than the traditional MC-based method, whereas the visual quality and quantitative accuracy of the reconstructed images are much better than that obtained by using the simplified system matrix alone. Conclusions: The residual correction method can reconstruct high-resolution images and is computationally efficient.

Original languageEnglish (US)
Pages (from-to)704-713
Number of pages10
JournalMedical Physics
Volume37
Issue number2
DOIs
StatePublished - 2010

Keywords

  • Iterative image reconstruction
  • On-the-fly Monte Carlo simulation
  • Positron range modeling
  • Residual correction

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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