Respiratory noise correction using phase information.

  • Cheng H
  • Li Y
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Abstract

Respiratory noise is a confounding factor in functional magnetic resonance
imaging (MRI) data analysis. A novel method called Respiratory noise
Correction using Phase information is proposed to retrospectively
correct for the respiratory noise in functional MRI (fMRI) time series.
It is demonstrated that the respiratory movement and the phase of
functional MRI images are highly correlated in time. The signal fluctuation
due to respiratory movements can be effectively estimated from the
phase variation and removed from the functional MRI time series using
a Wiener filtering technique. In our experiments, this new method
is compared with RETROICOR, which requires recording respiration
signal simultaneously in an fMRI experiment. The two techniques show
comparable performance with respect to the respiratory noise correction
for fMRI time series. However, this technique is more advantageous
because there is no need for monitoring the subjects' respiration
or changing functional MRI protocols. This technique is also potentially
useful for correcting respiratory noise from abnormal breathing or
when the respiration is not periodic.

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Authors

  • Hu Cheng

  • Yu Li

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