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Adaptive non-local means denoising of MR images with spatially varying noise levels.: Spatially Adaptive Non-Local Denoising
Abstract : PURPOSE: To adapt the so-called nonlocal means filter to deal with magnetic resonance (MR) images with spatially varying noise levels (for both Gaussian and Rician distributed noise). MATERIALS AND METHODS: Most filtering techniques assume an equal noise distribution across the image. When this assumption is not met, the resulting filtering becomes suboptimal. This is the case of MR images with spatially varying noise levels, such as those obtained by parallel imaging (sensitivity-encoded), intensity inhomogeneity-corrected images, or surface coil-based acquisitions. We propose a new method where information regarding the local image noise level is used to adjust the amount of denoising strength of the filter. Such information is automatically obtained from the images using a new local noise estimation method. RESULTS: The proposed method was validated and compared with the standard nonlocal means filter on simulated and real MRI data showing an improved performance in all cases. CONCLUSION: The new noise-adaptive method was demonstrated to outperform the standard filter when spatially varying noise is present in the images.
Cited literature [23 references]
https://www.hal.inserm.fr/inserm-00454564
Contributor : Pierrick Coupé <>
Submitted on : Monday, November 28, 2011 - 3:53:47 PM
Last modification on : Thursday, March 12, 2020 - 3:06:33 PM
Document(s) archivé(s) le : Wednesday, February 29, 2012 - 2:20:14 AM
Contributor : Pierrick Coupé <>
Submitted on : Monday, November 28, 2011 - 3:53:47 PM
Last modification on : Thursday, March 12, 2020 - 3:06:33 PM
Document(s) archivé(s) le : Wednesday, February 29, 2012 - 2:20:14 AM
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