摘要
针对三维超声图像去噪,提出一种新的各向异性扩散滤波算法。该算法主要通过改进传统算法中的扩散系数以及瞬时变化系数(ICOV),在保留三维超声图像边缘和细节的同时,更好地滤除了斑点噪声。与传统算法相比,该算法对迭代次数有更低的敏感度和更好的鲁棒性。
We proposed a new anisotropic diffusion filtering algorithm for 3D ultrasound images denoising. It filters the speckle noises better while preserving image's edges and details mainly by modifying diffusion coefficient and instantaneous coefficient of variation( ICOV)in conventional algorithm. Compared with conventional algorithm,the algorithm has lower sensitivity and better robustness on the number of iterations.
出处
《计算机应用与软件》
CSCD
2016年第11期135-138,143,共5页
Computer Applications and Software
基金
国家自然科学基金项目(31201121)
关键词
三维超声图像
各向异性扩散
斑点去噪
鲁棒性
3D ultrasound image
Anisotropic diffusion
Speckle reduction
Robustness
