• Login
    View Item 
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    One-Step Optimization of Adaptive SPECT Systems

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    azu_etd_16135_sip1_m.pdf
    Size:
    3.481Mb
    Format:
    PDF
    Download
    Author
    Ghanbari, Nasrin
    Issue Date
    2018
    Keywords
    adaptive systems
    optimization
    Scanning Linear Estimator
    SPECT
    Advisor
    Clarkson, Eric
    
    Metadata
    Show full item record
    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
    In this dissertation a method for one-step optimization of an adaptive Single Photon Emission Computed Tomography (SPECT) system is presented. Adaptive imaging systems can quickly change their hardware configuration in response to data being generated in order to improve image quality. The approach to assessment of image quality is based on the usefulness of images for performing a given task. The performance is measured by calculating a scalar quantity known as the figure of merit. The optimization algorithm, which aims at finding the optimal figure of merit, could either alter the system continuously during acquisition, or it could apply the one-step adaptation method presented by Barrett et al. which is adopted in this work. Prior to the optimization, the adaptive SPECT system is modeled by a ray tracing module. The system matrices for a selection of imaging configurations are simulated and stored. Access to this information expedites the optimization process, however it limits the solution space to a discrete set of adaptations. Depending on the size of the solution space we utilize either the grid search or the genetic algorithm to find the optimum adaptation. The optimization strategy is to find the adaptation that maximizes the performance on a signal estimation task. To start with, a simulated object model containing a spherical signal is imaged with a scout configuration. A Markov-Chain Monte Carlo (MCMC) technique utilizes the scout data to generate an ensemble of possible objects consistent with the scout data. This object ensemble is imaged by numerous simulated hardware configurations and for each system estimates of signal activity, size and location are calculated via the Scanning Linear Estimator (SLE). A figure of merit, based on a Modified Dice Index (MDI), quantifies the performance of each imaging configuration. This figure of merit is calculated by multiplying two terms: the first term uses the definition of the Dice similarity index to determine the percent of overlap between the actual and the estimated spherical signal, the second term utilizes an exponential function that measures the squared error for the activity estimate. The MDI combines the error in estimates of activity, size, and location, in one convenient metric and it allows for simultaneous optimization of the SPECT system with respect to all the estimated signal parameters. The average MDI for the object ensemble is a scalar value that quantifies the performance of a particular imaging configuration. The results of our optimizations indicate that adaptive systems perform better than non-adaptive in conditions where the diagnostic scan has a low photon count which makes this method suitable for conducting dynamic studies. Furthermore, this method can be used as a tool to evaluate the impact of design trade offs prior to the construction of adaptive systems. Examples of design trade-off include fixing the number of projection angles or adding multiplexing capability to the pinhole apertures. The most important contribution, which makes all the subsequent optimization results and design analysis possible, is the parallel implementation of SLE that can compute a figure of merit for a single configuration in 30 to 60 seconds.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Optical Sciences
    Degree Grantor
    University of Arizona
    Collections
    Dissertations

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.