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Author Dekker, A. J. Den ♦ Sijbers, J.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Neural Activity ♦ Non-gaussian Distributed Noise ♦ Rician Distribution ♦ Fmri Study ♦ Magnitude Image Reconstruction ♦ Statistical Fmri Test ♦ Monte Carlo Simulation ♦ Generalized Likelihood Ratio Test ♦ Functional Magnetic Resonance Imaging ♦ Stimulus Presentation ♦ Significant Neural Activity ♦ Magnitude Fmri Data ♦ Hemodynamic Response ♦ Magnitude Mri Data ♦ Brain Activation
Description Proc. EUROSIPCO
Functional magnetic resonance imaging (fMRI) measures the hemodynamic response in the brain that signals neural activity. The purpose is to detect those regions in the brain that show significant neural activity upon stimulus presentation. Most statistical fMRI tests used for this purpose rely on the assumption that the noise disturbing the data is Gaussian distributed. However, the major-ity of fMRI studies employ magnitude image reconstructions that are known to be Rician distributed, and hence corrupted by non-Gaussian distributed noise. In this work, we propose a Generalized Likelihood Ratio Test (GLRT) for magnitude MRI data that exploits the knowledge of the Rician distribution. The performance of the proposed GLRT is evaluated by means of Monte Carlo simulations. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2004-01-01