Respiratory noise correction using phase information

by Hu Cheng, Yu Li
Magnetic Resonance Imaging ()
Get full text at journal

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. ?? 2010 Elsevier Inc.

Author-supplied keywords

Cite this document (BETA)

Readership Statistics

10 Readers on Mendeley
by Discipline
 
40% Medicine
 
20% Engineering
 
10% Biological Sciences
by Academic Status
 
50% Post Doc
 
30% Ph.D. Student
 
20% Researcher (at an Academic Institution)
by Country
 
10% Germany
 
10% Italy
 
10% Denmark

Sign up today - FREE

Mendeley saves you time finding and organizing research. Learn more

  • All your research in one place
  • Add and import papers easily
  • Access it anywhere, anytime

Start using Mendeley in seconds!

Sign up & Download

Already have an account? Sign in