Li Xiaoying, Liu Dongquan
College of Computer Science, Sichuan University, Chengdu 610065, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2011 Dec;28(6):1094-7, 1109.
In order to get real time ultrasound images with clear structure and improved contrast, an adaptive ultrasound sound speed optimization method based on image contrast analysis was investigated. It firstly introduced the dynamic beamforming of ultrasound system, as well as the definition of assumed system's sound speed and the true sound speed propagated in tissues the degrade image quality due to their mismatch was also discussed. After given the pixel gray level value based ultrasound image contrast ratio, the basic idea to precisely estimate the true sound speed for real time system sound speed was proposed. Algorithms have been verified both in tissue-mimicking phantoms with known sound speeds and in vivo ultrasound images, compared with other existing method. The testing results showed that this new method not only produced accurate sound speed for ultrasound image optimization, but also finely met the critical computation requirement for real time applications.
为了获得结构清晰、对比度提高的实时超声图像，研究了一种基于图像对比度分析的自适应超声声速优化方法。首先介绍了超声系统的动态波束形成，以及假定系统声速和在组织中传播的真实声速的定义，还讨论了由于两者不匹配而导致图像质量下降的问题。在给出基于像素灰度值的超声图像对比度比后，提出了精确估计实时系统声速真实声速的基本思想。与其他现有方法相比，该算法已在具有已知声速的仿组织体模和体内超声图像中得到验证。测试结果表明，这种新方法不仅能为超声图像优化产生准确的声速，而且能很好地满足实时应用的关键计算要求。
