Abstract
In this article two modified versions of a simple and recently proposed method which is known as linear minimum mean square error (LMMSE) estimator for denoising of magnetic resonance (MR) images are presented. In the introduced approaches the self-similarity and natural redundancy of the acquired MR image are considered to achieve the higher performance of unknown signal estimation. Since, the MR data are in a large majority 3D, the proposed methods are developed to deal with 3D volumes. The introduced methods are compared with related state-of-the-art schemes over both clinical and simulated MR data. The quantitative and qualitative results show their superior denoising ability.
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