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Fusion of EEG and fMRI Image Processing Analysis and Research

Author: FanZuo
Tutor: LiuJiCheng; BaiRongJie
School: Northeast University of Petroleum
Course: Electronics and Communication Engineering
Keywords: EEG analysis Functional Magnetic Resonance Imaging fMRI fusion of EEG and fMRI Independent Component Analysis ICA
CLC: TP391.41
Type: Master's thesis
Year: 2013
Downloads: 28
Quote: 0
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Abstract


Electroencephalogram and Functional Magnetic Resonance Imaging can scan brain imaging non.invasively. They are widely used in comprehensive scientific research field, such as cognitive neuroscience. The two imaging methods exist both advantages and disadvantages. Combining EEG with fMRI and learning from each other, can describe spatial information and temporal information at the same time. By making use of EEG-fMRI fusion technology, scanning high temporal and high spatial resolution of the imaging non.invasive simultaneously, locating activation of the source direction accurately in brain cognitive progressing, tracking dynamic procedure of brain neural activity, and researching the connectivity of several active regions, thereby, describing brain reflection dynamic procedure in different or disease conditions. This paper introduces EEG and fMRI single modal algorithm, application, main problem in research and technical drawbacks. Making use of ICA process signal data in the paper, eliminate noise jamming in source signal, and extract effective ideal independent component signal. Not only do simulation gain ideal results, but also reduce calculation program trivial details; Necessary brain wave shape is gained by utilizing SSVEP, frequency characteristics of EEG-SSVEP are extracted effectively through using FFT and BSS. This paper analyses EEG-fMRI fusion with SPM toolbox and two modal signals fusion with FIT fusion toolbox, the experimental results show that method is correct and effective. In the end, making a summing up of the full text and looking to the future.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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