Speckle reduction for ultrasound images using nonlinear multi-scale complex wavelet diffusion

Muhammad Shahin Uddin, M. Tahtali, A. Lambert, M. Pickering
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引用次数: 4

Abstract

Speckle noise is a major shortcoming of any type of ultrasound imaging. Hence, speckle reduction is vital in providing a better clinical diagnosis. The key objective of any speckle reduction algorithm is to attain a speckle free image, whilst preserving the important anatomical features. In this paper, we introduce a nonlinear multi-scale complex wavelet diffusion based algorithm for speckle reduction and sharp edge preservation of 2D ultrasound images. The proposed method exploits some useful features of the dual tree complex wavelet transform and nonlinear diffusion. Simulated experimental results demonstrate that our proposed algorithm significantly reduces speckle noise while preserving sharp edges without discernible distortions. The proposed approach performs better than the previous existing approaches in both qualitative and quantitative measures.
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基于非线性多尺度复小波扩散的超声图像斑点去除
斑点噪声是任何类型的超声成像的一个主要缺点。因此,减少斑点对于提供更好的临床诊断至关重要。任何散斑减少算法的关键目标是获得无散斑图像,同时保留重要的解剖特征。本文提出了一种基于非线性多尺度复小波扩散的二维超声图像散斑去除和锐边保留算法。该方法利用了对偶树复小波变换和非线性扩散的一些有用特性。仿真实验结果表明,本文提出的算法能够有效地降低散斑噪声,同时保持图像边缘锐利,且没有明显的失真。所提出的方法在定性和定量度量方面都优于以前现有的方法。
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