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

Ollinger, J M; Goggin, A S

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

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Abstract

The SAGE and ordered subsets algorithms have been proposed as fast methods to compute penalized maximum likelihood estimates in PET. We 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.

Authors:

Ollinger, J M; Goggin, A S ^[1]

Washington Univ., St. Louis, MO (United States)

Publication Date:: Tue Dec 31 00:00:00 EST 1996

OSTI Identifier:: 513258

Report Number(s):: CONF-961123-
CNN: Grant 1380;Grant CA54959; TRN: 97:014311

Resource Type:: Conference

Resource Relation:: Conference: Institute of Electrical and Electronic Engineers (IEEE) nuclear science symposium and medical imaging conference, Anaheim, CA (United States), 2-9 Nov 1996; Other Information: PBD: 1996; Related Information: Is Part Of 1996 IEEE nuclear science symposium - conference record. Volumes 1, 2 and 3; Del Guerra, A. [ed.]; PB: 2138 p.

Country of Publication:: United States

Language:: English

Subject:: 44 INSTRUMENTATION, INCLUDING NUCLEAR AND PARTICLE DETECTORS; 55 BIOLOGY AND MEDICINE, BASIC STUDIES; PHOTON COMPUTED TOMOGRAPHY; IMAGE PROCESSING; ALGORITHMS; THREE-DIMENSIONAL CALCULATIONS; MAXIMUM-LIKELIHOOD FIT

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                    Ollinger, J M, and Goggin, A S. Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm.  United States: N. p., 1996. 
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                    Ollinger, J M, & Goggin, A S. Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm.  United States.

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                    Ollinger, J M, and Goggin, A S. 1996.  
        "Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm".  United States.

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@article{osti_513258,

  title        = {Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm},

  author       = {Ollinger, J M and Goggin, A S},

  abstractNote = {The SAGE and ordered subsets algorithms have been proposed as fast methods to compute penalized maximum likelihood estimates in PET. We 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.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/513258},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Dec 31 00:00:00 EST 1996},

  month        = {Tue Dec 31 00:00:00 EST 1996}

}

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