Document Detail


Image segmentation and activity estimation for microPET (11)C-raclopride images using an expectation-maximum algorithm with a mixture of Poisson distributions.
MedLine Citation:
PMID:  21288690     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The objective of this study was to use a mixture of Poisson (MOP) model expectation maximum (EM) algorithm for segmenting microPET images. Simulated rat phantoms with partial volume effect and different noise levels were generated to evaluate the performance of the method. The partial volume correction was performed using an EM deblurring method before the segmentation. The EM-MOP outperforms the EM-MOP in terms of the estimated spatial accuracy, quantitative accuracy, robustness and computing efficiency. To conclude, the proposed EM-MOP method is a reliable and accurate approach for estimating uptake levels and spatial distributions across target tissues in microPET (11)C-raclopride imaging studies.
Authors:
Kuan-Hao Su; Jay S Chen; Jih-Shian Lee; Chi-Min Hu; Chi-Wei Chang; Yuan-Hwa Chou; Ren-Shyan Liu; Jyh-Cheng Chen
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-1-31
Journal Detail:
Title:  Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society     Volume:  -     ISSN:  1879-0771     ISO Abbreviation:  -     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2011-2-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8806104     Medline TA:  Comput Med Imaging Graph     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 Elsevier Ltd. All rights reserved.
Affiliation:
Department of Psychiatry, Taipei Veterans General Hospital and National Yang-Ming University, Taiwan, Republic of China; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taiwan, Republic of China.
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