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Enhancement of Medical Ultrasound Images Using Multiscale Discrete Shearlet Transform Based Thresholding

机译:基于多尺度离散Shearlet变换阈值的医学超声图像增强

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Feature preserved enhancement is of great interest in medical ultrasound images. Speckle is a main factor which affects the quality, contrast resolution and most importantly texture information present in ultrasound images and can make the post-processing difficult. This paper presents a new enhancement approach which is based on discrete shearlet transform (DST) and thresholding scheme. The DST, a new efficient multiscale geometric representation with the different features of anisotropy, localization, directionality and multiscale, is employed to provide effective representation of the noisy coefficients. Thresholding schemes are applied to the noisy DST coefficients to improve the denoising efficiency and preserve the edge features effectively with this consideration that blurring associated with speckle reduction should be less and fine details are enhanced/preserved properly for the visual enhancement of ultrasound images. The presented algorithm also helps to improve the visual quality of the ultrasound images. Experimental results demonstrate the ability of proposed method for noise suppression, feature and edge preservation defined in terms of different performance measures.
机译:保留特征的增强功能在医学超声图像中引起了极大的兴趣。斑点是影响质量,对比度分辨率以及最重要的是影响超声图像中存在的纹理信息的主要因素,并且可能使后处理变得困难。本文提出了一种新的增强方法,该方法基于离散剪切波变换(DST)和阈值方案。 DST是一种新型的高效多尺度几何表示形式,具有各向异性,局部性,方向性和多尺度的不同特征,可用于有效表示噪声系数。阈值方案应用于噪声DST系数,以提高去噪效率并有效地保留边缘特征,同时考虑到与斑点减少相关的模糊应该更少,并且为了增强超声图像的视觉效果,适当地增强/保留了精细的细节。提出的算法还有助于提高超声图像的视觉质量。实验结果证明了所提出的方法在不同性能指标下对噪声抑制,特征和边缘保留的定义能力。

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