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Magn Reson Imaging. 2015 Jan;33(1):124-33. doi: 10.1016/j.mri.2014.08.028. Epub 2014 Aug 28.

A simple noise correction scheme for diffusional kurtosis imaging.

Author information

1
Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurosciences, Medical University of South Carolina, Charleston, SC, USA. Electronic address: glenng@musc.edu.
2
Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

Abstract

PURPOSE:

Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis.

METHODS:

Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates.

RESULTS:

As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR.

CONCLUSION:

The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms.

KEYWORDS:

Brain; Diffusion; Kurtosis; Noise; Phantom; Rician

PMID:
25172990
PMCID:
PMC4268031
DOI:
10.1016/j.mri.2014.08.028
[Indexed for MEDLINE]
Free PMC Article

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