Estimation of Response Functions Based on Variational Bayes Algorithm in Dynamic Images Sequences.
We proposed a nonparametric Bayesian model based on variational Bayes algorithm to estimate the response functions in dynamic medical imaging. In dynamic renal scintigraphy, the impulse response or retention functions are rather complicated and finding a suitable parametric form is problematic. In t...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 10 |
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| Autor principal: | |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/18/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117520406&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117520406 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/18/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 117520406 117520406 117520406 10.1155/2016/4851401 117520406 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Estimation of Response Functions Based on Variational Bayes Algorithm in Dynamic Images Sequences. aug: au: Shan, Bowei affil: School of Information Engineering, Chang’an University, Shaanxi 710064, China sug: subj: Algorithms Radionuclide Imaging Kidney Diseases Diagnosis Probability Models, Statistical Descriptive Statistics Funding Source ab: We proposed a nonparametric Bayesian model based on variational Bayes algorithm to estimate the response functions in dynamic medical imaging. In dynamic renal scintigraphy, the impulse response or retention functions are rather complicated and finding a suitable parametric form is problematic. In this paper, we estimated the response functions using nonparametric Bayesian priors. These priors were designed to favor desirable properties of the functions, such as sparsity or smoothness. These assumptions were used within hierarchical priors of the variational Bayes algorithm. We performed our algorithm on the real online dataset of dynamic renal scintigraphy. The results demonstrated that this algorithm improved the estimation of response functions with nonparametric priors. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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