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Wavelet and fast bilateral filter based de-speckling method for medical ultrasound images

机译:基于小波和快速双边滤波器的医学超声图像去斑方法

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Speckle noise is an undesirable part of the ultrasound imaging process, since it can degrade the quality of ultrasound images and restrict the development of automatic diagnostic techniques for ultrasound images. Aiming at the problem of speckle noise, an improved de-speckling method for medical ultrasound images is proposed, which is based on the wavelet transformation and fast bilateral filter. According to the statistical properties of medical ultrasound image in the wavelet domain, an improved wavelet threshold function based on the universal wavelet threshold function is considered. The wavelet coefficients of noise-free signal and speckle noise are modeled as generalized Laplace distribution and Gaussian distribution, respectively. The Bayesian maximum a posteriori estimation is applied to obtain a new wavelet shrinkage algorithm. High-pass component speckle noise in the wavelet domain of ultrasound images is suppressed by the new shrinkage algorithm. Additionally, the coefficients of the low frequency signal in the wavelet domain are filtered by the fast bilateral filter, since the low-pass component of ultrasound images also contains some speckle noise. Compared with other de-speckling methods, experiments show that the proposed method has improved de-speckling performance for medical ultrasound images. It not only has better reduction performance than other methods but also can preserve image details such as the edge of lesions. (C) 2014 Elsevier Ltd. All rights reserved.
机译:斑点噪声是超声成像过程中不可取的部分,因为它会降低超声图像的质量并限制超声图像自动诊断技术的发展。针对斑点噪声问题,提出了一种基于小波变换和快速双边滤波的医学超声图像去斑方法。根据小波域医学超声图像的统计特性,考虑基于通用小波阈值函数的改进小波阈值函数。将无噪声信号和斑点噪声的小波系数分别建模为广义拉普拉斯分布和高斯分布。应用贝叶斯最大值后验估计获得新的小波收缩算法。新的收缩算法抑制了超声图像小波域中的高通分量斑点噪声。另外,由于超声图像的低通分量还包含一些斑点噪声,因此小波域中的低频信号的系数被快速双边滤波器滤波。与其他去斑点方法相比,实验表明该方法对医学超声图像具有更好的去斑点性能。它不仅具有比其他方法更好的还原性能,而且可以保留图像细节(例如病灶边缘)。 (C)2014 Elsevier Ltd.保留所有权利。

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