• Find People
  • Campus Map
  • PiratePort
  • A-Z
    • About
    • Submit
    • Browse
    • Login
    View Item 
    •   ScholarShip Home
    • Dissertations and Theses
    • Dissertations
    • View Item
    •   ScholarShip Home
    • Dissertations and Theses
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of The ScholarShipCommunities & CollectionsDateAuthorsTitlesSubjectsTypeDate SubmittedThis CollectionDateAuthorsTitlesSubjectsTypeDate Submitted

    My Account

    Login

    Statistics

    View Google Analytics Statistics

    Generation of Pseudo-CT using Two Sets of MRI Scans for MRI-only Radiation Therapy

    Thumbnail
    View/ Open
    LEU-DOCTORALDISSERTATION-2019.pdf (22.08Mb)

    Show full item record
    Author
    Leu, Samuel C
    Abstract
    WWith increasing interests in magnetic resonance imaging (MRI)-only radiation therapy (RT) and the emergence of MRI system integrated with the linear accelerator, a method substituting the computed tomography (CT) in radiation therapy is required. The method to substitute the CT is by generating a pseudo-CT (pCT). A CT is necessary to provide the electron density information and to calculate the simulated dose distribution in treatment plans. In this thesis, a voxel-based method is developed to generate the pCT image using two sets of MRI data. The method is trained with the CT data and two different sets of MRI data of multiple patients, where the anatomical structures in the images are segmented into several regions. A regression analysis is used to determine the two-variable polynomial function for each region to relate a voxel's two MRI intensity values to its CT number. This method is validated by applying a leave-one-out-cross-validation (LOOCV) and the accuracy of the pCT is evaluated by determining the mean absolute error (MAE) comparing the pseudo-CT to the reference-CT. The average MAE across all patients is 40.3 ± 3.0 Hounsfield Unit (HU). Our proposed method shows promising results in using a multi-variable polynomial prediction model to predict CT numbers from MRI images. The generated pCT images closely match the reference-CT image and the MAE results are comparable to other studies using more complicated methods.
    URI
    http://hdl.handle.net/10342/7423
    Subject
     Pseudo-CT; Voxel-based method 
    Date
    2019-07-16
    Citation:
    APA:
    Leu, Samuel C. (July 2019). Generation of Pseudo-CT using Two Sets of MRI Scans for MRI-only Radiation Therapy (Doctoral Dissertation, East Carolina University). Retrieved from the Scholarship. (http://hdl.handle.net/10342/7423.)

    Display/Hide MLA, Chicago and APA citation formats.

    MLA:
    Leu, Samuel C. Generation of Pseudo-CT using Two Sets of MRI Scans for MRI-only Radiation Therapy. Doctoral Dissertation. East Carolina University, July 2019. The Scholarship. http://hdl.handle.net/10342/7423. April 21, 2021.
    Chicago:
    Leu, Samuel C, “Generation of Pseudo-CT using Two Sets of MRI Scans for MRI-only Radiation Therapy” (Doctoral Dissertation., East Carolina University, July 2019).
    AMA:
    Leu, Samuel C. Generation of Pseudo-CT using Two Sets of MRI Scans for MRI-only Radiation Therapy [Doctoral Dissertation]. Greenville, NC: East Carolina University; July 2019.
    Collections
    • Dissertations
    • Physics
    Publisher
    East Carolina University

    xmlui.ArtifactBrowser.ItemViewer.elsevier_entitlement

    East Carolina University has created ScholarShip, a digital archive for the scholarly output of the ECU community.

    • About
    • Contact Us
    • Send Feedback