DocumentCode :
2583341
Title :
Rician noise removal in MR images using an adaptive trilateral filter
Author :
Chang, Herng-Hua ; Hsieh, Tung-Ju ; Ting, Yun-Ni ; Chu, Woei-Chyn
Author_Institution :
Dept. of Eng. Sci. & Ocean Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume :
1
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
467
Lastpage :
471
Abstract :
Noise removal in MR images has been challenging due to the unpleasant noise with a Rician distribution, which is signal dependent. Denoising of MR images is of importance for subsequent diagnoses and analyses, such as tissue classification, segmentation, and registration. We propose a post-acquisition denoising algorithm to adequately and adaptively remove the random fluctuations and bias introduced by Rician noise. The proposed filter consists of geometric, radiometric, and median-metric components that replaces the intensity value with an weighted average between neighboring pixels associated with an entropy function. In addition, a parameter automation mechanism is proposed to reduce the burden of laborious interventions through a fuzzy membership function, which adaptively responses to local intensity difference. Quantitatively and qualitatively experimental results indicate that this new filter outperformed several existing methods in providing greater noise reduction and clearer structure boundaries in a variety of MR images.
Keywords :
adaptive filters; biomedical MRI; entropy; image resolution; medical image processing; noise; MR image; Rician noise removal; adaptive trilateral filter; entropy function; fuzzy membership function; local intensity difference; neighboring pixel; parameter automation mechanism; post-acquisition denoising algorithm; Anisotropic magnetoresistance; Image restoration; Noise reduction; PSNR; Radiometry; Rician channels; MRI; Rician noise; anisotropic diffusion filter; bilateral filter; denoising; fuzzy; trilateral filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9351-7
Type :
conf
DOI :
10.1109/BMEI.2011.6098281
Filename :
6098281
Link To Document :
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