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Ripplet domain non-linear filtering for speckle reduction in ultrasound medical images

机译:用于超声医学图像斑点减少的Ripplet域非线性滤波

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摘要

Ultrasound imaging is one of the most important and cheapest instrument used for diagnostic purpose among the clinicians. Due to inherent limitations of acquisition methods and systems, ultrasound images are corrupted by the multiplicative speckle noise that degrades the quality and most importantly texture information present in the ultrasound image. In this paper, we proposed an algorithm based on a new multiscale geometric representation as discrete ripplet transform and non-linear bilateral filter in order to reduce the speckle noise in ultrasound images. Ripplet transform with their different features of anisotropy, localization, directionality and multiscale is employed to provide effective representation of the noisy coefficients of log transformed ultrasound images. Bilateral filter is applied to the approximation ripplet coefficients to improve the denoising efficiency and preserve the edge features effectively. The performance of the proposed method is evaluated by conductive extensive simulations using both synthetic speckled and real ultrasound images. Experiments show that the proposed method provides better results of removing the speckle and preserving the edges and image details as compared to several existing methods.
机译:超声成像是临床医生中用于诊断目的的最重要和最便宜的仪器之一。由于采集方法和系统的固有局限性,超声图像被成倍的斑点噪声破坏,斑点噪声降低了质量,最重要的是降低了超声图像中存在的纹理信息。在本文中,我们提出了一种基于新的多尺度几何表示的算法,该离散离散纹波变换和非线性双边滤波器可以减少超声图像中的斑点噪声。利用具有各向异性,局域性,方向性和多尺度不同特征的Ripplet变换来有效表示对数变换后的超声图像的噪声系数。对近似纹波系数应用双边滤波器,以提高去噪效率并有效保留边缘特征。通过使用合成斑点图像和真实超声图像进行广泛的传导模拟,评估了所提出方法的性能。实验表明,与几种现有方法相比,该方法在去除斑点,保留边缘和图像细节方面具有更好的效果。

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