An improved statistical approach to the estimation of spatial bias and variability in reconstructed PET data

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Abstract

THE spatial bias and covariance characteristics of reconstructed PET data are important as routine assessments of image quality in PET scanners [4], [5]. Our previous empirical analysis of uniform Phantom data across the 43 sites in ACRIN [2] shows that both spatial bias and covariance can be decomposed as a product of a trans-axial radial function and axial function [1]. On the basis of this decomposition, we develop a penalised maximum likelihood type approach for analysis of bias and variance patterns. This can be viewed as a variation on the Π-method of Brieman [3]. The proposed approach is evaluated using a simulation model and demonstrated on PET data collected on an operationally used clinical PET scanner with the dynamic Brain ACRIN imaging protocol [2].

Original languageEnglish
Title of host publication2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467398626
DOIs
Publication statusPublished - 3 Oct 2016
Event2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015 - San Diego, United States
Duration: 31 Oct 20157 Nov 2015

Publication series

Name2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015

Conference

Conference2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
Country/TerritoryUnited States
CitySan Diego
Period31/10/157/11/15

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