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CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
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A BAYESIAN PET RECONSTRUCTION METHOD USING SEGMENTED ANATOMICAL MEMBRANE AS PRIORS
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GONG Tie-zhu, WANG Yuan-mei. A BAYESIAN PET RECONSTRUCTION METHOD USING SEGMENTED ANATOMICAL MEMBRANE AS PRIORS[J]. Journal of Zhejiang University Science A, 2001, 2(4): 406-410.
@article{title="A BAYESIAN PET RECONSTRUCTION METHOD USING SEGMENTED ANATOMICAL MEMBRANE AS PRIORS",
author="GONG Tie-zhu, WANG Yuan-mei",
journal="Journal of Zhejiang University Science A",
volume="2",
number="4",
pages="406-410",
year="2001",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2001.0406"
}
%0 Journal Article
%T A BAYESIAN PET RECONSTRUCTION METHOD USING SEGMENTED ANATOMICAL MEMBRANE AS PRIORS
%A GONG Tie-zhu
%A WANG Yuan-mei
%J Journal of Zhejiang University SCIENCE A
%V 2
%N 4
%P 406-410
%@ 1869-1951
%D 2001
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2001.0406
TY - JOUR
T1 - A BAYESIAN PET RECONSTRUCTION METHOD USING SEGMENTED ANATOMICAL MEMBRANE AS PRIORS
A1 - GONG Tie-zhu
A1 - WANG Yuan-mei
J0 - Journal of Zhejiang University Science A
VL - 2
IS - 4
SP - 406
EP - 410
%@ 1869-1951
Y1 - 2001
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2001.0406
Abstract: In this paper a fully Bayesian PET reconstruction method is presented for combining a segmented anatomical membrane a priori. The prior distributions are based on the fact that the radiopharmaceutical activity is similar throughout each region and the anatomical information is obtained from other imaging modalities such as CT or MRI. The prior parameters in prior distribution are considered drawn from hyperpriors for fully bayesian reconstruction. Dynamic markov chain monte carlo methods are used on the Hoffman brain phantom to gain estimates of the posterior mean. The reconstruction result is compared to those obtained by ML, MAP. Our results showed that the segmented anatomical membrane a priori exhibit improved the noise and resolution properties.
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