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

Conference · Tue Dec 31 00:00:00 EST 1996

OSTI ID:513258

Ollinger, J M; Goggin, A S ^[1]

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

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.

• OSTI ID: 513258
• Report Number(s): CONF-961123-; CNN: Grant 1380; Grant CA54959; TRN: 97:014311
• 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

Related Subjects

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