摘要
针对医学超声图像中声衰减补偿引起的组织结构模糊、清晰度降低问题,提出一种基于引导滤波的自适应优化超声图像方法.首先分析声衰减对医学超声成像能量的影响;其次比较超声信号能量补偿常用方法,选用图像纹理信息进行衰减补偿;再结合引导滤波保边平滑特性,根据超声图像组织结构与斑点噪声均值与方差特性自适应优化,得到具有更多临床诊断信息的高品质超声图像.实验结果表明,该方法改善了图像清晰度,在增强图像组织结构的同时弱化斑点噪声,其有效性在仿真体模、正常与病变组织的超声图中得到了验证.
To reduce structure blurring and clarity degradation in medical ultrasound images due to acoustic attenuation, we propose a novel adaptive optimization method based on guided filtering. Firstly, the influence of acoustic attenuation for medical image is analyzed. Secondly, the texture information of the image is selected to compensate for the acoustic attenuation after comparison of some ultrasonic pulse-echo compensation methods. Then, due to the edge-preserving and smoothing performance in guided filtering, by combining the mean and variance, it can be used to optimize the regions of structure and speckle noise. High quality ultrasound images with more clinical diagnosis aided information are obtained. The experimental results show that the adaptive method has excellent capability of improving the image clarity, enhancing the structure and reducing the speckle noise. The effect of the proposed method is proved in phantom, in vivo normal and lesion ultrasound images.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2014年第1期40-46,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家"九七三"重点基础研究发展计划项目(2009CB320803)
四川省科技支撑项目(2013GZX0147-3)
关键词
声衰减
增益补偿
引导滤波
超声图像清晰度
acoustic attenuation
gain compensation
guided filter
ultrasound image clarity degree