A Non-Local Rician Noise Reduction Approach for 3-D Magnitude Magnetic Resonance Images

2011 ◽  
Author(s):  
Hosein M. Golshan ◽  
Reza PR. Hasanzadeh
Keyword(s):  
Magnetic Resonance ◽  
Noise Reduction ◽  
Magnetic Resonance Images ◽  
Rician Noise ◽  
Non Local ◽  
Reduction Approach

Noise reduction in magnetic resonance images using adaptive non‐local means filtering

2013 ◽  
Vol 49 (5) ◽  
pp. 324-326 ◽  
Author(s):  
B. Kang ◽  
O. Choi ◽  
J.D. Kim ◽  
D. Hwang
Keyword(s):  
Magnetic Resonance ◽  
Noise Reduction ◽  
Magnetic Resonance Images ◽  
Local Means ◽  
Non Local

scholarly journals Implementation of Iterative bilateral filtering for removal of Rician noise in MR images using FPGA

2020 ◽  
Vol 9 (3) ◽  
pp. 279-284
Keyword(s):  
Magnetic Resonance ◽  
Real Time ◽  
Visual Analysis ◽  
Similarity Index ◽  
Structural Similarity ◽  
Bilateral Filter ◽  
Magnetic Resonance Images ◽  
Rician Noise ◽  
Diagnostic Quality ◽  
Index Matrix

Magnetic resonance image noise reduction is important to process further and visual analysis. Bilateral filter is denoises image and also preserves edge. It proposes Iterative bilateral filter which reduces Rician noise in the magnitude magnetic resonance images and retains the fine structures, edges and it also reduces the bias caused by Rician noise. The visual and diagnostic quality of the image is retained. The quantitative analysis is based on analysis of standard quality metrics parameters like peak signal-to-noise ratio and mean structural similarity index matrix reveals that these methods yields better results than the other proposed denoising methods for MRI. Problem associated with the method is that it is computationally complex hence time consuming. It is not recommended for real time applications. To use in real time application a parallel implantation of the same using FPGA is proposed.

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