Analysis Of Functional Magnetic Resonance Image Sequences Based On Brain Motion Control

The functional brain imaging aims at finding the higher brain function such as mechanism hidden behind cognition and cortical information processing. Many techniques have been proposed for statistically analyzing fMRI data, like statistical parametric mapping, periodogram, multi-taper spectrum estimation, independent component analysis, correlated coefficients methods, and so on. This paper emphatically discusses some problems met in the application research about detecting activation regions by multifarious statistically analyzing methods.As far as statistical parametric mapping(SPM) and independent component analysis(ICA) are concerned, each has its strong prospect. In the process of practical analysis, it' s difficult to educe the advantages and disadvantages of two techniques and inosculate them. The 1st chapter gives an introduction. The 2nd chapter of this paper proposes a survey for functional brain imaging based on studying about one hundred related articles, then the 3rd chapter introduces the functional magnetic resonance imaging(fMRI). In the 4th chapter, the principle and analytic process of SPM are analyzed. The 5th chapter is the application of the technique, the chapter presents the analysis of the fMRI dataset by SPM and the discussion about combination of SPM and ICA. The 6th chapter studies the application of spectral estimation theory including periodogram and multi-taper spectral estimation in the detecting activation. At the end of the paper, based on the analysis and comparison, key factors in functional brain imaging are concluded and distilled as suggestion to future research.