Positron Emission Tomography Compartmental Models: A Basis Pursuit Strategy for Kinetic Modeling
نویسندگان
چکیده
منابع مشابه
Positron emission tomography compartmental models: a basis pursuit strategy for kinetic modeling.
A kinetic modeling approach for the quantification of in vivo tracer studies with dynamic positron emission tomography (PET) is presented. The approach is based on a general compartmental description of the tracer's fate in vivo and determines a parsimonious model consistent with the measured data. The technique involves the determination of a sparse selection of kinetic basis functions from an...
متن کاملPositron Emission Tomography Compartmental Models: A Basis Pursuit Strategy for Kinetic Modelling
A kinetic modelling approach for the quantification of in vivo tracer studies with dynamic positron emission tomography (PET) is presented. The approach is based on a general compartmental description of the tracer’s fate in vivo and determines a parsimonious model consistent with the measured data. The technique involves the determination of a sparse selection of kinetic basis functions from a...
متن کاملPositron emission tomography compartmental models.
The current article presents theory for compartmental models used in positron emission tomography (PET). Both plasma input models and reference tissue input models are considered. General theory is derived and the systems are characterized in terms of their impulse response functions. The theory shows that the macro parameters of the system may be determined simply from the coefficients of the ...
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Most PET kinetic modeling approaches have at their basis a compartmental model that has first-order, constant coefficients. The present article outlines the one-, two-, and three-compartment models used to measure cerebral blood flow, cerebral glucose metabolism, and receptor binding, respectively. The number of compartments of each model is based on specific knowledge of the physiological and/...
متن کاملBayesian Model Comparison for Compartmental Models with Applications in Positron Emission Tomography
We develop strategies for Bayesian modelling as well as model comparison, averaging and selection for compartmental models with particular emphasis on those which occur in the analysis of Positron Emission Tomography (PET) data. Both modelling and computational issues are considered. It is shown that an additive normal error structure does not describe measured PET data well and that within a s...
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ژورنال
عنوان ژورنال: Journal of Cerebral Blood Flow & Metabolism
سال: 2002
ISSN: 0271-678X,1559-7016
DOI: 10.1097/01.wcb.0000045042.03034.42