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

被引：0
|
作者：
Ollinger, JM
Goggin, AS
机构：
来源：
1996 IEEE NUCLEAR SCIENCE SYMPOSIUM - CONFERENCE RECORD, VOLS 1-3 | 1997年
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D O I：
暂无
中图分类号：
TL [原子能技术]; O571 [原子核物理学];
学科分类号：
0827 ; 082701 ;
摘要：
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.
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页码：1594 / 1598
页数：5
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