Impact on Image Noise of Incorporating Detector Blurring Into Image Reconstruction for a Small Animal PET Scanner

被引：6
|
作者：
Lee, Kisung [1 ]
Miyaoka, Robert S. [2 ]
Lewellen, Tom K. [2 ]
Alessio, Adam M. [2 ]
Kinahan, Paul E. [2 ]
机构：
[1] Korea Univ, Dept Radiol Sci, Seoul 136703, South Korea
[2] Univ Washington, Dept Radiol, Seattle, WA 98195 USA
来源：
IEEE TRANSACTIONS ON NUCLEAR SCIENCE | 2009年 / 56卷 / 05期
基金：
美国国家卫生研究院;
关键词：
Detector blurring; Fourier rebinning; noise property; ordered subsets expectation maximization (OSEM); positron emission tomography; RESOLUTION; ALGORITHMS; EM;
D O I：
10.1109/TNS.2009.2021610
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We study the noise characteristics of an image reconstruction algorithm that incorporates a model of the non-stationary detector blurring (DB) for a mouse-imaging positron emission tomography (PET) scanner. The algorithm uses ordered subsets expectation maximization (OSEM) image reconstruction., which is used to suppress statistical noise. Including the non-stationary detector blurring in the reconstruction process [OSEM(DB)] has been shown to increase contrast in images reconstructed from measured data acquired on the fully-3D MiCES PET scanner developed at the University of Washington. As an extension, this study uses simulation studies with a fully-3D acquisition mode and our proposed FORE+OSEM(DB) reconstruction process to evaluate the volumetric contrast versus noise trade-offs of this approach. Multiple realizations were simulated to estimate the true noise properties of the algorithm. The results show that incorporation of detector blurring FORE+OSEM(DB) into the reconstruction process improves the contrast/noise trade-offs compared to FORE+OSEM in a radially dependent manner. Adding post reconstruction 3D Gaussian smoothing to FORE+OSENT and FORE+OSEM(DB) reduces the contrast versus noise advantages of FORE+OSEM(DB).
引用
收藏
页码：2769 / 2776
页数：8
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