Persistent Link:
http://hdl.handle.net/10150/278351
Title:
Expectation maximization methods for processing SPECT images
Author:
Marcotte, Hope Ann, 1964-
Issue Date:
1993
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
A method is developed for pre-processing projection images for a SPECT brain imaging system. The projection images are recorded by modular gamma cameras that exhibit noisy response before processing. The image acquisition process is modeled so that the mean of the detected gamma-ray emissions is a linear transformation of the actual flux. Two models for detection are examined, one based on independent Poisson distributions and the other based on a multivariate distribution. The Expectation Maximization (EM) algorithm is used to invert the forward model to obtain a Maximum Likelihood estimate of the flux. Simulations using uniform, Gaussian and point flux patterns demonstrated that EM processing recovered improved estimates of these patterns. Processing measured images yielded improved estimates, but also revealed that both forward models are incomplete.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Engineering, Biomedical.; Engineering, Electronics and Electrical.; Health Sciences, Radiology.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Barrett, Harrison H.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleExpectation maximization methods for processing SPECT imagesen_US
dc.creatorMarcotte, Hope Ann, 1964-en_US
dc.contributor.authorMarcotte, Hope Ann, 1964-en_US
dc.date.issued1993en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractA method is developed for pre-processing projection images for a SPECT brain imaging system. The projection images are recorded by modular gamma cameras that exhibit noisy response before processing. The image acquisition process is modeled so that the mean of the detected gamma-ray emissions is a linear transformation of the actual flux. Two models for detection are examined, one based on independent Poisson distributions and the other based on a multivariate distribution. The Expectation Maximization (EM) algorithm is used to invert the forward model to obtain a Maximum Likelihood estimate of the flux. Simulations using uniform, Gaussian and point flux patterns demonstrated that EM processing recovered improved estimates of these patterns. Processing measured images yielded improved estimates, but also revealed that both forward models are incomplete.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectEngineering, Biomedical.en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectHealth Sciences, Radiology.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorBarrett, Harrison H.en_US
dc.identifier.proquest1353137en_US
dc.identifier.bibrecord.b27959132en_US
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