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

机译:改进的非局部均值滤波器可有效减少超声图像中的斑点

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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.
机译:由于其无创性,低成本,形成实时成像的能力以及图像质量的不断提高,超声成像是一种广泛使用且安全的医学诊断技术。然而;由于存在依赖于信号的噪声(称为斑点),超声成像的实用性会降低。众所周知,斑点是一种乘性噪声,会降低超声成像的视觉评价。在超声(US)成像中,去噪旨在改善定量图像分析技术。在本文中,基于相似度函数,提出了一种适用于美国图像的新版本的非局部(NL-)均值滤波器,该函数取决于超声图像中方差斑点噪声的特定特征。将该方法与中位数,小波,均值和方差局部统计,几何,各向异性扩散滤波和使用定量参数的非局部均值滤波进行了比较。根据在真实图像上获得的视觉结果和图像质量评估指标,我们可以得出结论:改进的(NL-)表示滤波器可以成功用于超声图像去噪,并且比所有其他方法执行的效果更好,同时仍保留了结构细节并保留了消除斑点噪声的同时,边缘和纹理也非常好。

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