Laplacian based non-local means denoising of MR images with Rician noise
DSpace at IIT Bombay
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Title |
Laplacian based non-local means denoising of MR images with Rician noise
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Creator |
BHUJLE, HV
CHAUDHURI, S |
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Subject |
Magnetic Resonance Imaging
Laplacian of Gaussian Nonlocal-means Rician noise MAGNETIC-RESONANCE IMAGES MAXIMUM-LIKELIHOOD-ESTIMATION ANISOTROPIC DIFFUSION ALGORITHM REMOVAL NEIGHBORHOODS RATIO |
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Description |
Magnetic Resonance (MR) image is often corrupted with a complex white Gaussian noise (Rician noise) which is signal dependent. Considering the special characteristics of Rician noise, we carry out nonlocal means denoising on squared magnitude images and compensate the introduced bias. In this paper, we propose an algorithm which not only preserves the edges and fine structures but also performs efficient, denoising. For this purpose we have used a Laplacian of Gaussian (LOG) filter in conjunction with a nonlocal means filter (NLM). Further, to enhance the edges and to accelerate the filtering process, only a few similar patches have been preselected on the basis of closeness in edge and inverted mean values. Experiments have been conducted on both simulated and clinical data sets. The qualitative and quantitative measures demonstrate the efficacy of the proposed method. (C) 2013 Elsevier Inc. All rights reserved.
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Publisher |
ELSEVIER SCIENCE INC
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Date |
2014-10-17T04:38:34Z
2014-10-17T04:38:34Z 2013 |
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Type |
Article
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Identifier |
MAGNETIC RESONANCE IMAGING, 31(9)1599-1610
0730-725X 1873-5894 http://dx.doi.org/10.1016/j.mri.2013.07.001 http://dspace.library.iitb.ac.in/jspui/handle/100/15969 |
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Language |
en
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