DocumentCode
1396772
Title
Consolidation of common parameters from multiple fits in dynamic PET data analysis
Author
Huesman, Ronald H. ; Coxson, Pamela G.
Author_Institution
California Univ., Berkeley, CA, USA
Volume
16
Issue
5
fYear
1997
Firstpage
675
Lastpage
683
Abstract
In dynamic positron emission tomography (PET) data analysis, regions of interest (ROIs) are analyzed by fitting a parametric model to the time-activity curve acquired after a radio-labeled tracer has been introduced into the patient´s bloodstream. This procedure can be carried out for multiple ROIs and/or multiple injections of the same or a different radiopharmaceutical. The approach presented here takes advantage of prior knowledge that some of the parameters of those multiple fits are the same. Reduction of the total number of parameters to be estimated results in smaller statistical uncertainty for all parameter estimates, especially those common to multiple fits.
Keywords
maximum likelihood estimation; medical image processing; parameter estimation; positron emission tomography; common parameters consolidation; dynamic PET data analysis; medical diagnostic imaging; multiple fits; multiple injections; nuclear medicine; parametric model fitting; patient´s bloodstream; radiolabeled tracer; radiopharmaceutical; regions of interest; statistical uncertainty; time-activity curve; Approximation methods; Biomedical imaging; Blood; Curve fitting; Data analysis; Maximum likelihood estimation; Parameter estimation; Parametric statistics; Positron emission tomography; Uncertainty; Algorithms; Animals; Artifacts; Brain; Glucose; Humans; Image Processing, Computer-Assisted; Likelihood Functions; Models, Biological; Models, Statistical; Radionuclide Ventriculography; Radiopharmaceuticals; Time Factors; Tomography, Emission-Computed;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/42.640758
Filename
640758
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