Multiscale Nonlinear Diffusion and Shock Filter for Ultrasound Image Enhancement

Fan Zhang, Y. Yoo, Yongmin Kim, Lichen Zhang, L. M. Koh
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引用次数: 15

Abstract

A new noise reduction and edge enhancement method, i.e., Laplacian pyramid-based nonlinear diffusion and shock filter (LPNDSF), is proposed for medical ultrasound imaging. In the proposed LPNDSF, a coupled nonlinear diffusion and shock filter process is applied in Laplacian pyramid domain of an image, to remove speckle and enhance edges simultaneously. The performance of the proposed method was evaluated on a phantom and a real ultrasound image. In the phantom study, we obtained an average gain of 0.55 and 1.11 in contrast-to-noise ratio compared to the speckle reducing anisotropic diffusion (SRAD) and nonlinear coherent diffusion (NCD), respectively. Also, the proposed LPNDSF showed clearer boundaries on the phantom and the real ultrasound image. These preliminary results indicate that the proposed LPNDSF can effectively reduce speckle noise while enhancing image edges for retaining subtle features.
超声图像增强的多尺度非线性扩散和冲击滤波
提出了一种新的医学超声成像降噪和边缘增强方法,即基于拉普拉斯金字塔的非线性扩散和冲击滤波(LPNDSF)。在该算法中,在图像的拉普拉斯金字塔域采用非线性扩散和冲击耦合滤波处理,同时去除斑点和增强边缘。在仿真和真实超声图像上对该方法的性能进行了评价。在模体研究中,与散斑减少各向异性扩散(SRAD)和非线性相干扩散(NCD)相比,我们分别获得了0.55和1.11的平均增益。此外,所提出的LPNDSF在虚影和真实超声图像上的边界更清晰。这些初步结果表明,所提出的LPNDSF可以有效地降低散斑噪声,同时增强图像边缘以保留细微特征。
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