• Login
    View Item 
    •   MINDS@UW Home
    • MINDS@UW Milwaukee
    • UW Milwaukee Electronic Theses and Dissertations
    • View Item
    •   MINDS@UW Home
    • MINDS@UW Milwaukee
    • UW Milwaukee Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Accelerating MRI Data Acquisition Using Parallel Imaging and Compressed Sensing

    Thumbnail
    File(s)
    Main File (6.595Mb)
    Date
    2012-12-01
    Author
    Wang, Haifeng
    Department
    Engineering
    Advisor(s)
    Jun Zhang
    Metadata
    Show full item record
    Abstract
    Magnetic Resonance Imaging (MRI) scanners are one of important medical instruments, which can achieve more information of soft issues in human body than other medical instruments, such as Ultrasound, Computed Tomography (CT), Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), etc. But MRI's scanning is slow for patience of doctors and patients. In this dissertation, the author proposes some methods of parallel imaging and compressed sensing to accelerate MRI data acquisition. Firstly, a method is proposed to improve the conventional GRAPPA using cross-sampled auto-calibration data. This method use cross-sampled auto-calibration data instead of the conventional parallel-sampled auto-calibration data to estimate the linear kernel model of the conventional GRAPPA. The simulations and experiments show that the cross-sampled GRAPPA can decrease the quantity of ACS lines and reduce the aliasing artifacts comparing to the conventional GRAPPA under same reduction factors. Secondly, a Hybrid encoding method is proposed to accelerate the MRI data acquisition using compressed sensing. This method completely changes the conventional Fourier encoding into Hybrid encoding, which combines the benefits of Fourier and Circulant random encoding, under 2D and 3D situation, through the proposed special hybrid encoding pulse sequences. The simulations and experiments illustrate that the images can be reconstructed by the proposed Hybrid encoding method to reserve more details and resolutions than the conventional Fourier encoding method. Thirdly, a pseudo 2D random sampling method is proposed by dynamically swapping the gradients of x and y axes on pulse sequences, which can be implemented physically as the convention 1D random sampling method. The simulations show that the proposed method can reserve more details than the convention 1D random sampling method. These methods can recover images to achieve better qualities under same situations than the conventional methods. Using these methods, the MRI data acquisitions can be accelerated comparing to the conventional methods.
    Subject
    Circulant Random Encoding
    Compressed Sensing
    GRAPPA
    MRI
    Parallel Imaging
    Pulse Sequence
    Permanent Link
    http://digital.library.wisc.edu/1793/91972
    Type
    dissertation
    Part of
    • UW Milwaukee Electronic Theses and Dissertations

    Contact Us | Send Feedback
     

     

    Browse

    All of MINDS@UWCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    Login

    Contact Us | Send Feedback