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Journal of Medical Imaging • Open Access

Noise distribution and denoising of current density images
Author(s): Mohammadali Beheshti; Farbod H. Foomany; Karl Magtibay; David A. Jaffray; Sridhar Krishnan; Kumaraswamy Nanthakumar; Karthikeyan Umapathy

Paper 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 (J). The minimum gain in noise power by BM3D applied to J 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.

Paper Details

Date Published: 14 May 2015
PDF: 10 pages
J. Med. Img. 2(2) 024005 doi: 10.1117/1.JMI.2.2.024005
Published in: Journal of Medical Imaging Volume 2, Issue 2
Show Author Affiliations
Mohammadali Beheshti, Ryerson Univ. (Canada)
Farbod H. Foomany, Ryerson Univ. (Canada)
Karl Magtibay, Ryerson Univ. (Canada)
David A. Jaffray, Princess Margaret Cancer Ctr. (Canada)
Sridhar Krishnan, Ryerson Univ. (Canada)
Kumaraswamy Nanthakumar, Toronto General Hospital (Canada)
Karthikeyan Umapathy, Ryerson Univ. (Canada)


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