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

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 rul...

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Bibliographic Details
Authors: Llacer, Jorge, Veklerov, Eugene, Coakley, Kevin J., Hoffman, Edward J., Núñez de Murga, Jorge, 1955-
Format: article
Status:Published version
Publication Date:1993
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/8544
Online Access:https://hdl.handle.net/2445/8544
Access Level:Open access
Keyword:Cervell
Tomografia d'emissió
Estadística
Brain
Computerised tomography
Radioisotope scanning and imaging
Statistical analysis
Description
Summary: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.