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Noise distribution and denoising of current density images
Mohammadali Beheshti1, Farbod H Foomany1, Karl Magtibay1
1Ryerson University , Electrical and Computer Engineering Department, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada.
Abstract:
Current density imaging (CDI) is a magnetic resonance (MR) imaging technique that could be used to study current pathways inside the tissue. The current distribution is measured indirectly as phase changes. The inherent noise in the MR imaging technique degrades the accuracy of phase measurements leading to imprecise current variations. The outcome can be affected significantly, especially at a low signal-to-noise ratio (SNR). We have shown the residual noise distribution of the phase to be Gaussian-like and the noise in CDI images approximated as a Gaussian. This finding matches experimental results. We further investigated this finding by performing comparative analysis with denoising techniques, using two CDI datasets with two different currents (20 and 45 mA). We found that the block-matching and three-dimensional (BM3D) technique outperforms other techniques when applied on current density ([Formula: see text]). The minimum gain in noise power by BM3D applied to [Formula: see text] compared with the next best technique in the analysis was found to be around 2 dB per pixel. We characterize the noise profile in CDI images and provide insights on the performance of different denoising techniques when applied at two different stages of current density reconstruction.
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