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Edge Probability and Pixel Relativity-Based Speckle Reducing Anisotropic Diffusion

机译:边缘概率和基于像素相关性的散斑减少各向异性扩散

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摘要

Anisotropic diffusion filters are one of the best choices for speckle reduction in the ultrasound images. These filters control the diffusion flux flow using local image statistics and provide the desired speckle suppression. However, inefficient use of edge characteristics results in either oversmooth image or an image containing misinterpreted spurious edges. As a result, the diagnostic quality of the images becomes a concern. To alleviate such problems, a novel anisotropic diffusion-based speckle reducing filter is proposed in this paper. A probability density function of the edges along with pixel relativity information is used to control the diffusion flux flow. The probability density function helps in removing the spurious edges and the pixel relativity reduces the oversmoothing effects. Furthermore, the filtering is performed in superpixel domain to reduce the execution time, wherein a minimum of 15% of the total number of image pixels can be used. For performance evaluation, 31 frames of three synthetic images and 40 real ultrasound images are used. In most of the experiments, the proposed filter shows a better performance as compared to the state-of-the-art filters in terms of the speckle region's signal-to-noise ratio and mean square error. It also shows a comparative performance for figure of merit and structural similarity measure index. Furthermore, in the subjective evaluation, performed by the expert radiologists, the proposed filter's outputs are preferred for the improved contrast and sharpness of the object boundaries. Hence, the proposed filtering framework is suitable to reduce the unwanted speckle and improve the quality of the ultrasound images.
机译:各向异性扩散滤镜是减少超声图像中斑点的最佳选择之一。这些滤波器使用局部图像统计数据控制扩散通量流,并提供所需的斑点抑制。但是,边缘特征的低效使用会导致图像过于平滑或图像包含误解的虚假边缘。结果,图像的诊断质量成为问题。为了缓解这些问题,本文提出了一种新型的基于各向异性扩散的斑点减少滤波器。边缘的概率密度函数与像素相关性信息一起用于控制扩散通量。概率密度函数有助于消除虚假边缘,而像素相关性则减少了过度平滑的影响。此外,在超像素域中执行滤波以减少执行时间,其中可以使用图像像素总数的至少15%。为了进行性能评估,使用了31帧三幅合成图像和40幅实际超声图像。在大多数实验中,在斑点区域的信噪比和均方误差方面,与最先进的滤波器相比,所提出的滤波器表现出更好的性能。它还显示了品质因数和结构相似性度量指标的比较性能。此外,在由放射线专家进行的主观评估中,建议的滤光片输出对于改善对象边界的对比度和清晰度是优选的。因此,所提出的滤波框架适合于减少不需要的斑点并改善超声图像的质量。

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