Statistical Analysis of Noise in MRI by Santiago Aja-Fernández & Gonzalo Vegas-Sánchez-Ferrero

Author:Santiago Aja-Fernández & Gonzalo Vegas-Sánchez-Ferrero
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

7.1.2 Estimators Based on the Signal Area

The estimators presented so far are based on the probability distribution of the background of the image. However, there are occasions in which this background is not available due to different issues: the acquisition does not include a background, the background has been eliminated or there are not enough points to carry out an accurate estimation. In those cases, the estimation must be done over the signal area of the image. The main problem of this kind of estimation is that the moments of the Rician distribution depend on the original signal value , which initially is unknown and depends on the position. This parameter can be reformulated as a dependence with the SNR in each point, which is also an unknown parameter. Thus, estimators that rely on the signal area, must find a way to carry out the noise estimation without a direct dependency with this parameter.

Rician Estimators Based on Local Variance

Assuming that all the data are Rician distributed, no Rayleigh background is present, and the SNR is high enough, typically , the following estimator may be defined [3]

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.