Real valued diffusion-weighted imaging using decorrelated phase filtering

Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine
Tim SprengerMarion I Menzel

Abstract

Because of the intrinsic low signal-to-noise ratio in diffusion-weighted imaging (DWI), magnitude processing often causes an overestimation of the signal's amplitude. This results in low-estimation accuracy of diffusion models and reduced contrast because of a superposition of the image signal and the noise floor. We adopt a new phase correction (PC) technique that yields real valued diffusion data while maintaining a Gaussian noise distribution. We conduct simulations of the noise propagation in the echo-planar imaging reconstruction chain to determine the spatial noise correlation in the image. Using the correlation pattern, optimized filter kernels are derived to estimate the true phase of the signal in each voxel. Furthermore, we adopt an outlier detection technique to replace the real value by the magnitude in case of substantial signal loss resulting from incorrect PC. The benefits of our method are demonstrated on Monte Carlo simulations, DWI data acquired from healthy volunteer experiments, estimated parameters of the diffusion kurtosis imaging model, and the model-free diffusion spectrum imaging technique. The improved PC approach significantly reduces the noise bias and only slightly increases the sensitivity to local...Continue Reading

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Citations

Mar 1, 2017·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Jonathan I SperlLuca Marinelli
Oct 11, 2017·IEEE Transactions on Medical Imaging·Inaki RabanilloDiego Hernando
Nov 2, 2017·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Stefan SkareMathias Engström
Sep 20, 2018·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Iñaki Rabanillo-ViloriaDiego Hernando

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