Modified non-local means filter for effective speckle reduction in ultrasound images

B. A. Abrahim, Z. A. Mustafa, Y. Kadah
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引用次数: 11

Abstract

Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, capability of forming real time imaging, and the continuing improvements in image quality. However; the usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. It is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. In ultrasound (US) imaging, denoising is intended to improve quantitative image analysis techniques. In this paper, a new version of the Non Local (NL-) means filter adapted for US images is proposed based on Similarity function depend on specific characteristics of the variance speckle noise in ultrasound images. The proposed method has been compared with Median, Wavelet, Mean and variance local statistics, Geometric, Anisotropic diffusion filtering, and Non ' local means filter using quantitative parameters. From the visual results and image quality evaluation metrics obtained over real images we can conclude that the modified(NL-) means filter can be successfully used for ultrasound image denoising, and performs better results than all other methods while still retaining the structural details and retains the edges and textures very well while removing speckle noise.
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改进的非局部均值滤波器能有效地去除超声图像中的斑点
超声成像具有无创、成本低、能够实时成像、图像质量不断提高等优点,是一种应用广泛、安全的医学诊断技术。然而;超声成像的有用性被称为散斑的信号依赖噪声的存在所降低。众所周知,斑点是一种乘法噪声,降低了超声成像的视觉评价。在超声成像中,去噪是为了改进定量图像分析技术。本文根据超声图像中方差散斑噪声的具体特征,基于相似函数,提出了一种新的适用于超声图像的非局部均值滤波方法。将该方法与中值、小波、均值和方差局部统计、几何、各向异性扩散滤波和非局部均值滤波进行了比较。从对真实图像的视觉结果和图像质量评价指标可以得出结论,改进的(NL-)均值滤波器可以成功地用于超声图像去噪,并且在保留结构细节的同时,在去除斑点噪声的同时很好地保留了边缘和纹理,效果优于所有其他方法。
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