• Login
    View Item 
    •   IDA Home
    • Students -- Research, Data, Projects, and Papers
    • Student Theses and Honors Collection
    • View Item
    •   IDA Home
    • Students -- Research, Data, Projects, and Papers
    • Student Theses and Honors Collection
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Designing Simulated Radio Frequency Ultrasound Traces for the Training of Machine Learning Algorithms

    Thumbnail
    View/Open
    NBrandt_Thesis.pdf (1.372Mb)
    Date
    2019-06-24
    Author
    Brandt, Naomi
    Metadata
    Show full item record
    Abstract
    In the field of ultrasound imaging, it has been theorized that imaging noise, known as speckle, is the product of microscopic scatterers and abnormalities within the imaged tissue. This would result in certain speckling patterns revealing themselves over large datasets, which could be utilized to identify minuscule lesions within tissues, potentially creating a method to predict the early formation of tumors. Such a dataset would be difficult to analyze by hand, but machine learning algorithms could be used to recognize patterns in a effective manner. As of now, few attempts have been made to utilize machine learning in order to predict scatterer placement from ultrasound scans. In order to initiate machine learning, first a computational simulation must be constructed to consistently and accurately reproduce experimental data. Using Field II, a MATLAB-based program for ultrasound modelling, simulations were created to replicate data produced from experimental phantoms made from glass beads and agarose gel. These simulations were designed to account for bead placement and size, as well as experimental conditions. Comparisons between simulations and experimental data using statistical analysis show that ultrasound images can accurately be predicted using computational methods. With these software programs, it becomes possible to train a machine learning algorithm to recognize speckling pattern, which may allow for the resolution of previously unresovable scatterers.
    URI
    http://hdl.handle.net/10166/5701
    Collections
    • Student Theses and Honors Collection

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback | MHC Accessibility Barriers Form
    Theme by 
    @mire NV
     

     

    Browse

    All of IDACommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback | MHC Accessibility Barriers Form
    Theme by 
    @mire NV