• DocumentCode
    1621725
  • Title

    Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm

  • Author

    Ollinger, John M. ; Goggin, Andrew S.

  • Author_Institution
    Washington Univ., St. Louis, MO, USA
  • Volume
    3
  • fYear
    1996
  • Firstpage
    1594
  • Abstract
    The SAGE and ordered subsets algorithms have been proposed as fast methods to compute penalized maximum likelihood estimates in PET. The authors have implemented both for use in fully 3D PET and completed a preliminary evaluation. The technique used to compute the transition matrix is fully described. The evaluation suggests that the ordered subsets algorithm converges much faster than SAGE, but that it stops short of the optimal solution
  • Keywords
    image reconstruction; maximum likelihood estimation; medical image processing; positron emission tomography; SAGE algorithm; fully 3D PET; maximum likelihood reconstruction; medical diagnostic imaging; nuclear medicine; optimal solution; ordered subsets algorithms; transition matrix; Cancer; Computational complexity; Convergence; Eigenvalues and eigenfunctions; Face detection; Image converters; Image reconstruction; Iterative algorithms; Maximum likelihood estimation; Positron emission tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium, 1996. Conference Record., 1996 IEEE
  • Conference_Location
    Anaheim, CA
  • ISSN
    1082-3654
  • Print_ISBN
    0-7803-3534-1
  • Type

    conf

  • DOI
    10.1109/NSSMIC.1996.587929
  • Filename
    587929