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Rician noise removal in magnitude MRI images using efficient anisotropic diffusion filtering
Author(s) -
Pal Chandrajit,
Das Pabitra,
Chakrabarti Amlan,
Ghosh Ranjan
Publication year - 2017
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22230
Subject(s) - rician fading , computer science , anisotropic diffusion , noise (video) , noise reduction , artificial intelligence , computer vision , diffusion mri , median filter , filter (signal processing) , magnitude (astronomy) , artifact (error) , diffusion , magnetic resonance imaging , algorithm , image processing , image (mathematics) , physics , radiology , medicine , decoding methods , fading , thermodynamics , astronomy
In this article, a new methodology for denoising of Rician noise in Magnetic Resonance Images (MRI) is presented. MRI imaging creates a distinctive view into the interior of a human body and has become an essential tool of clinical diagnosis. However, Rician noise is a type of artifact inherent to the acquisition process of the magnitude MRI image, making diagnosis difficult. We proposed a moment‐based Rician noise reduction technique in anisotropic diffusion filtering. We extend the work of the classical anisotropic diffusion filter and have customized it to remove Rician noise in the magnitude MRI image in 3D domain space. Our proposed scheme shows better results against various quality measures in terms of noise removal and edge preservation while retaining fine textures.