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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