DocumentCode
3629717
Title
Principles of image reconstruction using Positron Emission Tomography and maximum likelihood estimation algorithms
Author
Milan Bezbradica;Zeljen Trpovski
Author_Institution
Energotehnika Ju?na Ba?ka, Department of Informatics, Put Novosadskog Partizanskog odreda 1, 21000 Novi Sad, Serbia
fYear
2008
Firstpage
141
Lastpage
144
Abstract
Positron emission tomography (PET) is used extensively in image acquisition for medical purposes. It is necessary to perform an evaluation of parameters that are required for image reconstruction based on the measured data. The most commonly used method for estimation of PET parameters is Expectation Maximization algorithm. About a decade ago a new SAGE algorithm was developed and soon it began to be used in image reconstruction. Principles and examples of these algorithms as well as of PET are described in this paper.
Keywords
"Image reconstruction","Positron emission tomography","Maximum likelihood estimation","Detectors","Parameter estimation","Iterative algorithms","Event detection","Biomedical imaging","Radioactive decay","Neural networks"
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering, 2008. NEUREL 2008. 9th Symposium on
Print_ISBN
978-1-4244-2903-5
Type
conf
DOI
10.1109/NEUREL.2008.4685592
Filename
4685592
Link To Document