Functional Magnetic Resonance Imaging Processing by Xingfeng Li

By Xingfeng Li

With robust numerical and computational concentration, this ebook serves as a necessary source at the equipment for useful neuroimaging research, diffusion weighted picture research, and longitudinal VBM research. It contains 4 MRI picture modalities research tools. the 1st covers the PWI equipment, that is the root for realizing cerebral circulation in human mind. the second one half, the book’s middle, covers fMRI equipment in 3 particular domain names: first point research, moment point research, and potent connectivity research. The 3rd half covers the research of Diffusion weighted snapshot, i.e. DTI, QBI and DSI photograph research. eventually, the e-book covers (longitudinal) VBM tools and its software to Alzheimer’s sickness research.

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5 General Linear Model (GLM) for Activation Detection . . . . . . . . . . . . . . . . . . 1 Generalized Linear Model (GLM) for Activation Detection . . . . . . . . . . . 2 Ordinary Least Square for Parameter Estimation in GLM . . . . . . . . . . . . . 3 FOS to Solve the Inverse Problem . . . . . . . . . . . . . . . . . . . . . . . . . 4 Weighted Least Squares Estimation. . . . . . . . . . . . . . . . .

3 FOS to Solve the Inverse Problem . . . . . . . . . . . . . . . . . . . . . . . . . 4 Weighted Least Squares Estimation. . . . . . . . . . . . . . . . . . . . . . . . . 5 AR(1) Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 AR(q) Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Hypothesis Test and Threshold Correction .

48 2 First-Level fMRI Data Analysis for Activation Detection Fig. 7 An example of fMRI response to the phase-encoded spatial frequency experimental design For functional images, we perform image registration to correct head movement during data collection within each run and across different runs. In the literature of image registration, many methods have been developed. For example, correlation method, linear and nonlinear least squares methods, and mutual information methods have been developed.

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