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Matches in SemOpenAlex for { <https://semopenalex.org/work/W2016359237> ?p ?o ?g. }

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• W2016359237 abstract "This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time–activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation." @default.
• W2016359237 created "2016-06-24" @default.
• W2016359237 creator A5021572716 @default.
• W2016359237 creator A5061737582 @default.
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• W2016359237 date "2008-05-06" @default.
• W2016359237 modified "2023-09-23" @default.
• W2016359237 title "Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET" @default.
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• W2016359237 doi "https://doi.org/10.1088/0031-9155/53/11/008" @default.
• W2016359237 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18460748" @default.
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