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Rician noise removal in magnitude MRI images using efficient anisotropic diffusion filtering |
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| Authors: | Chandrajit Pal Pabitra Das Amlan Chakrabarti Ranjan Ghosh |
| Affiliation: | 1. A.K. Choudhury School of Information Technology, University of Calcutta, JD‐2, Sector III, Salt Lake City, Kolkata, India;2. Institute of Radio Physics and Electronics, University of Calcutta, JD‐2, Sector III, Salt Lake City, Kolkata, India |
| Abstract: | 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. |
| Keywords: | diffusion coefficient edge preservation index mean square error moment‐based Rician noise reduction anisotropic diffusion quality index based on local variance Rician noise Rician variance second order moment structural similarity |
