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Variance stabilization of noncentral-chi data: Application to noise estimation in MRI | IEEE Conference Publication | IEEE Xplore

Variance stabilization of noncentral-chi data: Application to noise estimation in MRI


Abstract:

A variance-stabilizing transformation (VST) specifically designed for noncentral-chi (nc-x) data is presented. The VST is derived to generate Gaussian-like distributed va...Show More

Abstract:

A variance-stabilizing transformation (VST) specifically designed for noncentral-chi (nc-x) data is presented. The VST is derived to generate Gaussian-like distributed variates from nc-x data. Two methods are proposed: (1) an analytic asymptotic model for high SNR; and (2) a robust numerical model to improve the performance for low SNR. As an application and proof of concept, the VST is used for the estimation of non-stationary noise fields in multiple coil MRI acquisitions. It is validated over accelerated data reconstructed using GRAPPA. The method is compared to the main state-of-the-art methods. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.
Date of Conference: 13-16 April 2016
Date Added to IEEE Xplore: 16 June 2016
Electronic ISBN:978-1-4799-2349-6
Electronic ISSN: 1945-8452
Conference Location: Prague, Czech Republic

References

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