Spatial resolution properties of penalized-likelihood image reconstruction: Space-invariant tomographs

被引:428
作者
Fessler, JA
Rogers, WL
机构
[1] University of Michigan, Ann Arbor
基金
美国国家卫生研究院;
关键词
D O I
10.1109/83.535846
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper examines the spatial resolution properties of penalized-likelihood image reconstruction methods by analyzing the local impulse response. The analysis shows that standard regularization penalties induce space-variant local impulse response functions, even for space-invariant tomographic systems, Paradoxically, for emission image reconstruction, the local resolution is generally poorest in high-count regions. We show that the linearized local impulse response induced by quadratic roughness penalties depends on the object only through its projections. This analysis leads naturally to a modified regularization penalty that yields reconstructed images with nearly uniform resolution. The modified penalty also provides a very practical method for choosing the regularization parameter to obtain a specified resolution in images reconstructed by penalized-likelihood methods.
引用
收藏
页码:1346 / 1358
页数:13
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