Files
Document type
ArticleVersion
Published versionPublication date
All rights reserved
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/8544
Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies
Journal Title
Director/Tutor
Journal ISSN
Volume Title
Related resource
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.
Subject
Subject (English)
Citation
Citation
LLACER, Jorge, et al. Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies. IEEE Transactions on Medical Imaging. 1993. Vol. 12, num. 2, pags. 215-231. ISSN 0278-0062. [consulted: 9 of August of 2026]. Available at: https://hdl.handle.net/2445/8544