Fractional subpixel diffusion and fuzzy logic approach for ultrasound speckle reduction

被引:31
|
作者
Zhang, Yingtao [1 ]
Cheng, H. D. [1 ,2 ]
Tian, Jiawei [3 ]
Huang, Jianhua [1 ]
Tang, Xianglong [1 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Peoples R China
[2] Utah State Univ, Dept Comp Sci, Logan, UT 84322 USA
[3] Harbin Med Univ, Affiliated Hosp 2, Harbin, Peoples R China
基金
美国国家科学基金会;
关键词
Anisotropic diffusion; Subpixel; FSFPD (fuzzy subpixel fractional partial difference); Speckle reduction; Breast ultrasound (BUS) imaging; Fuzzy entropy; ANISOTROPIC DIFFUSION; CONTRAST ENHANCEMENT; BOUNDARY DETECTION; EDGE-DETECTION; SCALE-SPACE; IMAGES; NOISE; REMOVAL; MODEL;
D O I
10.1016/j.patcog.2010.02.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Speckle is the dominant source of noise in ultrasound imaging and is a kind of multiplicative noise. It is difficult to design a filter to remove speckle effectively. In this paper, a novel fuzzy subpixel fractional partial difference (FSFPD) for ultrasound speckle reduction is proposed. Euler-Lagrange equation acts as an increasing function of the fractional derivative's absolute value of the image intensity function. The fractional order partial difference is computed in the frequency and fuzzy domain with subpixel precision. We test the proposed method on both synthetic and real breast ultrasound (BUS) images. The comparisons of the experimental results show that the proposed method can preserve edges and structural details of ultrasound images well while removing speckle noise. In addition, the filtered images are assessed and evaluated by radiologists using double blind method. The results demonstrate that the discrimination rate of breast cancers has been highly improved after employing the proposed method. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2962 / 2970
页数:9
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