Noise Estimation in Multiple–Coil MR Data

  • Santiago Aja-Fernández
  • Gonzalo Vegas-Sánchez-Ferrero


The estimators presented in the previous chapter were focused on single-coil acquisitions. Here, we extend those results to the particular case of multiple-coil acquisitions in which the magnitude signal is reconstructed using Sum of Squares (SoS) or a Spatial matched filter (SMF). In addition, we assume that there exist no correlations among coils, and all of them show the same variance of noise. As a consequence, the magnitude signal follows a stationary noncentral- \(\chi \) distribution (nc-\(\chi \)) if SoS is used, or a stationary Rician one, in the case of SMF. We focus on the SoS case and the nc-\(\chi \) distribution, since the Rician case is studied in Chap.  7. The main noise estimators for the nc-\(\chi \) are thus reviewed and classified. Most of the methods proposed are basically extrapolations of the Rician estimators to the nc-\(\chi \). In the last part of the chapter, different estimators are compared and a performance analysis is done using synthetic and real data.


Covariance Ghost 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Santiago Aja-Fernández
    • 1
  • Gonzalo Vegas-Sánchez-Ferrero
    • 2
  1. 1.ETSI TelecomunicaciónUniversidad de ValladolidValladolidSpain
  2. 2.Harvard Medical SchoolBrigham and Womenʾs HospitalBostonUSA

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