Ultrasound speckle reduction by a SUSAN-controlled anisotropic diffusion method

被引:76
作者
Yu, Jinhua [1 ]
Tan, Jinglu [1 ]
Wang, Yuanyuan [2 ]
机构
[1] Univ Missouri, Dept Biol Engn, Columbia, MO 65211 USA
[2] Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China
关键词
Speckle reduction; Anisotropic diffusion; SUSAN; Nakagami distribution; Structure tensor; EDGE-DETECTION; NONLINEAR DIFFUSION; IMAGE-ENHANCEMENT; FILTER; MODEL; SUPPRESSION; DOMAIN; TIME;
D O I
10.1016/j.patcog.2010.04.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An ultrasound speckle reduction method is proposed in this paper. The filter, which enhances the power of anisotropic diffusion with the Smallest Univalue Segment Assimilating Nucleus (SUSAN) edge detector, is referred to as the SUSAN-controlled anisotropic diffusion (SUSAN_AD). The SUSAN edge detector finds image features by using local information from a pseudo-global perspective. Thanks to the noise insensitivity and structure preservation properties of SUSAN, a better control can be provided to the subsequent diffusion process. To enhance the adaptability of the SUSAN_AD, the parameters of the SUSAN edge detector are calculated based on the statistics of a fully formed speckle (FFS) region. Different FFS estimation schemes are proposed for envelope-detected speckle images and log-compressed ultrasonic images. Adaptive diffusion threshold estimation and automatic diffusion termination criterion are employed to enhance the robustness of the method. Both synthetic and real ultrasound images are used to evaluate the proposed method. The performance of the SUSAN_AD is compared with four other existing speckle reduction methods. It is shown that the proposed method is superior to other methods in both noise reduction and detail preservation. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3083 / 3092
页数:10
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