Noise suppression in brain magnetic resonance imaging based on non-local means filter and fuzzy cluster

被引：14

作者：

Liu, Bin ^{[1
,2
]}

Sang, Xinzhu ^{[1
]}

Xing, Shujun ^{[1
]}

Wang, Bo ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Minist Educ, Beijing 100876, Peoples R China

[2] Hebei Univ, Coll Elect & Informat Engn, Baoding 071002, Peoples R China

来源：

OPTIK | 2015年 / 126卷 / 21期

基金：

中国国家自然科学基金;

关键词：

Non-local means (NLM); Wavelet; Fuzzy cluster; Denoising; Brain magnetic resonance imaging (MRI); TRANSFORM;

D O I：

10.1016/j.ijleo.2015.07.056

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Combining Non-Local Means (NLM) filter with appropriate fuzzy cluster criterion, denoising in synthetic brain magnetic resonance imaging (MRI) are evaluated. Experimental results show that noise is effectively suppressed while image details are well kept, compared with the traditional NLM method and wavelet method. Quantitative and qualitative results indicate that the continuous edge and detailed structure are well preserved, artifacts are greatly reduced and brain MR images are typically enhanced. In addition, the computational time is reduced greatly. (C) 2015 Elsevier GmbH. All rights reserved.

引用

页码：2955 / 2959

页数：5

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