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    Generalized likelihood ratio detection for fMRI using complex data

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    Author
    Nan, F.Y.; Nowak, Robert David
    Date
    1999-04-20
    Abstract
    The majority of fMRI studies obtain functional information using statistical tests based on the magnitude image reconstructions. Recently, a complex correlation (CC) test was proposed based on teh complex image data in order to take advantage of phase information in teh signal. However, the CC test ignores additional phase information in the baseline component of the data. In this paper, a new detector for fMRI based on a Generalized Likelihood Ration Test (GLRT) is proposed. The GLRT exploits the fact that the fMRI response signal as well as the baseline component of the data share a common phase. Theoretical analysis and Monte Carlo simulation are used to explore the performance of the new detector. At relatively low signal intensities, the GLRT outperforms both the standard magnitude data test and the CC test. At high signal intensities, the GLRT performs as well as teh standard magnitude data test and significantly better than the CC test.
    Description
    Journal Paper
    Citation
    F. Nan and R. D. Nowak, "Generalized likelihood ratio detection for fMRI using complex data," IEEE Transactions on Medical Imaging, vol. 18, no. 4, 1999.
    Published Version
    http://dx.doi.org/10.1109/42.768841
    Keyword
    functional magnetic resonance imaging (fMRI); signal detection; statistics; hypothesis testing; image processing and pattern analysis; More... functional magnetic resonance imaging (fMRI); signal detection; statistics; hypothesis testing Less...
    Type
    Journal article
    Citable link to this page
    https://hdl.handle.net/1911/20130
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    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map