Parallel implementations of image reconstruction algorithms for emission tomography

Persistent Link:
http://hdl.handle.net/10150/277300
Title:
Parallel implementations of image reconstruction algorithms for emission tomography
Author:
Magee, Kathleen Ann, 1959-
Issue Date:
1990
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:
Techniques for implementing the EM and simulated-annealing image reconstruction algorithms on a large-grain parallel computer for faster execution per iteration are developed for emission tomography applications. The speedups obtained by implementing the algorithms on up to 54 processors connected in a ring topology are found to be nearly linear. Reconstruction involves finding an estimate of the emission distribution that minimizes an energy function that contains a data-agreement term and a noise-control term. The EM algorithm minimizes the complete-incomplete form of the data-agreement term, which is easily partitioned for parallel computation. The simulated-annealing algorithm is a Monte Carlo method in which any form of data-agreement and noise-control term can be minimized. In the reconstruction of a thyroid phantom, it is demonstrated that the complete-incomplete data-agreement term can be used to facilitate the parallel implementation of simulated annealing while still guaranteeing convergence.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Statistics.; Physics, Optics.; Computer Science.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Barrett, Harrision H.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleParallel implementations of image reconstruction algorithms for emission tomographyen_US
dc.creatorMagee, Kathleen Ann, 1959-en_US
dc.contributor.authorMagee, Kathleen Ann, 1959-en_US
dc.date.issued1990en_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.abstractTechniques for implementing the EM and simulated-annealing image reconstruction algorithms on a large-grain parallel computer for faster execution per iteration are developed for emission tomography applications. The speedups obtained by implementing the algorithms on up to 54 processors connected in a ring topology are found to be nearly linear. Reconstruction involves finding an estimate of the emission distribution that minimizes an energy function that contains a data-agreement term and a noise-control term. The EM algorithm minimizes the complete-incomplete form of the data-agreement term, which is easily partitioned for parallel computation. The simulated-annealing algorithm is a Monte Carlo method in which any form of data-agreement and noise-control term can be minimized. In the reconstruction of a thyroid phantom, it is demonstrated that the complete-incomplete data-agreement term can be used to facilitate the parallel implementation of simulated annealing while still guaranteeing convergence.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectStatistics.en_US
dc.subjectPhysics, Optics.en_US
dc.subjectComputer Science.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, Harrision H.en_US
dc.identifier.proquest1340294en_US
dc.identifier.bibrecord.b26252764en_US
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