• DocumentCode
    1127381
  • Title

    Partial volume effect compensation for quantitative brain SPECT imaging

  • Author

    Du, Yong ; Tsui, Benjamin M W ; Frey, Eric C.

  • Author_Institution
    Dept. of Radiol., Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    24
  • Issue
    8
  • fYear
    2005
  • Firstpage
    969
  • Lastpage
    976
  • Abstract
    Partial volume (PV) effects degrade the quantitative accuracy of SPECT brain images. In this paper, we extended a PV compensation (PVC) method originally developed for brain PET, the geometric transfer matrix (GTM) method, to brain SPECT using iterative reconstruction-based compensations. In the GTM method a linear transform between the true regional activities and the measured results was assumed. Elements of the GTM were calculated by projecting and reconstructing maps with uniform regions representing different structures. However, with iterative reconstruction methods, especially when reconstruction-based compensation for detector response was applied, we found that it was important to treat the region maps as a perturbation to the reconstructed image in the estimation of the GTM. This modified method, termed perturbation-based GTM (pGTM) was evaluated using Monte Carlo (MC) simulated and experimentally acquired data. Results showed great improvement of the quantitative accuracy in brain SPECT imaging. For MC simulated data, PVC using pGTM reduced the underestimation of striatal activities from 30% to less than 1.2%. For experimental data, PVC using pGTM reduced the underestimation of striatal activities from 36% to less than 7.8%. The underestimation of the striatum to background activity ratio was also improved from 31% to 2.7%.
  • Keywords
    Monte Carlo methods; brain; image reconstruction; iterative methods; medical image processing; perturbation techniques; single photon emission computed tomography; Monte Carlo method; brain SPECT imaging; iterative reconstruction-based compensations; partial volume effect compensation; perturbation-based geometric transfer matrix; striatal activities; Attenuation; Brain modeling; Degradation; Detectors; Diseases; Image reconstruction; Iterative methods; Positron emission tomography; Reconstruction algorithms; Scattering; Brain SPECT imaging; partial volume effect compensation; quantification; Algorithms; Artifacts; Artificial Intelligence; Brain; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity; Tomography, Emission-Computed, Single-Photon;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2005.850547
  • Filename
    1490666