• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
  • Help
    • Item Submission
    • Publisher policies
    • User guides
    • FAQs
  • About QSpace
    • Vision & Mission
    • QSpace policies
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Student Thesis & Dissertations
  • College of Arts & Sciences
  • Mathematics, Statistics & Physics
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Student Thesis & Dissertations
  • College of Arts & Sciences
  • Mathematics, Statistics & Physics
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    VARIOGRAM MODELING FOR SPATIAL CORRELATION IN STRUCTURAL MRI IMAGES

    Thumbnail
    View/Open
    Mara'Beh, Saed_OGA Approved Thesis.pdf (2.191Mb)
    Date
    06-2022
    Author
    MARA'BEH, SAED
    Metadata
    Show full item record
    Abstract
    In recent years neuroimaging techniques growth help us to understand the working of the human brain by using structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI). Structural MRIs are used to show the main structure of the brain organism such as gray matter, white matter, and cerebrospinal fluid (CSF). The functional MRI is used to study the brain activity when performing an assigned task like eyes moving and talking. It uses the bloodoxygen- level dependent (BOLD) contrast, when there is an activity in a region of the brain the blood flow to that area will increase. In this research, geostatistical techniques such as the variogram and kriging approaches are utilized to uncover the spatial correlation in structural magnetic resonance imaging (sMRI) data and to predict the effect of a brain tumor on brain regions. We propose different variogram models approach for three brain slices containing a brain tumor and we find that the best models for slices 10 and 11 is the exponential model and for slice 12 is the Gaussian model, the best model is selected by using the cross - validation method in kriging. A bootstrap resampling method is used to estimate the empirical variogram values and the parameters of the selected models.
    DOI/handle
    http://hdl.handle.net/10576/32128
    Collections
    • Mathematics, Statistics & Physics [‎28‎ items ]

    entitlement


    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    About QSpace

    Vision & Mission QSpace policies

    Help

    Item Submission Publisher policiesUser guides FAQs

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video