Wavelet-based statistical analysis of fMRI activation images
نویسنده
چکیده
R. Mutihac Electricity and Biophysics, University of Bucharest, Bucharest, Romania Objective Analysis of an fMRI block-based visual stimulation paradigm was comparatively performed by wavelet analysis and statistical parametric mapping (SPM) [1] based on Gaussian Random Field Theory (RFT). The voxels were isotropic and the same general linear model (GLM) was employed in both SPM and the discrete wavelet transform (DWT) approach. Consequently, an equivalent spline degree for which the low-pass part of the wavelet analysis is basically equivalent to SPM was computed. The results for two biorthogonal transforms, 3D fractional-spline wavelets and 2D+Z fractional quincunx wavelets, are presented comparatively with spatial smoothing in SPM.
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