Document Detail


Data analysis in emission tomography using emission-count posteriors.
MedLine Citation:
PMID:  23032513     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
A novel approach to the analysis of emission tomography data using the posterior probability of the number of emissions per voxel (emission count) conditioned on acquired tomographic data is explored. The posterior is derived from the prior and the Poisson likelihood of the emission-count data by marginalizing voxel activities. Based on emission-count posteriors, examples of Bayesian analysis including estimation and classification tasks in emission tomography are provided. The application of the method to computer simulations of 2D tomography is demonstrated. In particular, the minimum-mean-square-error point estimator of the emission count is demonstrated. The process of finding this estimator can be considered as a tomographic image reconstruction technique since the estimates of the number of emissions per voxel divided by voxel sensitivities and acquisition time are the estimates of the voxel activities. As an example of a classification task, a hypothesis stating that some region of interest (ROI) emitted at least or at most r-times the number of events in some other ROI is tested. The ROIs are specified by the user. The analysis described in this work provides new quantitative statistical measures that can be used in decision making in diagnostic imaging using emission tomography.
Authors:
Arkadiusz Sitek
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-03
Journal Detail:
Title:  Physics in medicine and biology     Volume:  57     ISSN:  1361-6560     ISO Abbreviation:  Phys Med Biol     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401220     Medline TA:  Phys Med Biol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  6779-6795     Citation Subset:  -    
Affiliation:
Radiology Department, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
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