Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies

Author

Llacer, Jorge ; Veklerov, Eugene ; Coakley, Kevin J. ; Hoffman, Edward J. ; Nunez, Jorge

Author_Institution

Lawrence Berkeley Lab., California Univ., CA, USA

Volume

12

Issue

2

fYear

1993

fDate

6/1/1993 12:00:00 AM

Firstpage

215

Lastpage

231

Abstract

The work presented evaluates the statistical characteristics of regional bias and expected error in reconstructions of real positron emission tomography (PET) data of human brain fluoro-deoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task of evaluating radioisotope uptake in regions-of-interest (ROIs) is investigated. An assessment of bias and variance in uptake measurements is carried out with simulated data. Then, by using three different transition matrices with different degrees of accuracy and a components of variance model for statistical analysis, it is shown that the characteristics obtained from real human FDG brain data are consistent with the results of the simulation studies

Keywords

brain; computerised tomography; radioisotope scanning and imaging; statistical analysis; components of variance model; expected error; filtered backprojection reconstructions; fluoro-deoxiglucose; human brain FDG PET studies; maximum likelihood estimator; medical diagnostic imaging; method of sieves; nuclear medicine; radioisotope uptake evaluation; regional bias; robust stopping rule; statistical characteristics; transition matrices; Brain modeling; Filtering; Humans; Image reconstruction; Kernel; Maximum likelihood estimation; Medical simulation; Positron emission tomography; Robustness; Statistical analysis;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/42.232250

Filename

232250