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Abstract #4146

Adjusted Nonlinear Registration in Spatial Normalization for Real-time fMRI

Xiaojie Zhao 1 , Xiaofei Li 1 , and Li Yao 1

1 College of Information Science and Technology, Beijing Normal University, Beijing, Beijing, China

As a common data preprocessing procedure for fMRI data, spatial normalization can provide abundant referential information for the brain region recognition. However, for real-time fMRI (rtfMRI), which requires the entire data processing within a single TR, spatial normalization is too time-consuming to include in the data preprocessing in rtfMRI. In this paper, we discussed the cutoff frequency and iteration number using bisection method in nonlinear registration of spatial normalization, proposed an adjusted nonlinear registration method to meet the real-time requirement of rtfMRI.

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