The rician distribution of noisy mri data

TLDR

Magnetic resonance magnitude image intensities follow a Rician distribution in the presence of noise. The study aims to estimate the underlying noise from images and provide a simple correction scheme to reduce bias. The authors estimate noise directly from the images and apply a simple correction to reduce bias. Low‑SNR intensities are biased, phase‑image noise differs from magnitude, yet both distributions approximate Gaussian when SNR exceeds two.

Abstract

Abstract The image intensity in magnetic resonance magnitude images in the presence of noise is shown to be governed by a Rician distribution. Low signal intensities (SNR < 2) are therefore biased due to the noise. it is shown how the underlying noise can be estimated from the images and a simple correction scheme is provided to reduce the bias. the noise characteristics in phase images are also studied and shown to be very different from those of the magnitude images. Common to both, however, is that the noise distributions are nearly Gaussian for SNR larger than two.