改进的最大似然期望最大化超声CT重建方法  

Ultrasonic CT reconstruction based on improved maximum likelihood expectation maximization algorithm

作　　者：赵子健[1] 常发亮[1] 李冰清[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《电子测量与仪器学报》2016年第9期1327-1332,共6页Journal of Electronic Measurement and Instrumentation

基　　金：高等学校博士学科点专项科研基金(20130131120036;20130131110038);山东省优秀中青年科学家科研奖励基金(BS2013DX027);中国自然科学基金(61273277;81401543);山东省科技重大专项(新兴产业)(2015ZDXX0801A01);山东大学基本科研业务费(自然科学专项)(2015QY001)资助项目

摘　　要：针对超声CT重建问题,提出了一种基于高斯分布的最大似然期望最大化方法,并采用非最小最优化的方法来设置迭代的初始值。由于高斯分布更加符合测得时间信息的分布规律,所以基于高斯分布的新算法比传统基于泊松分布的最大似然期望最大化算法更加精确。所采用的非最小最优化方法能够减少迭代次数,有利于提高重建质量和计算效率。为了检验新算法,对三维温度场进行了仿真重建实验,结果表明,改进后的最大似然期望最大化算法具有更小的平均误差,能够得到更精确的重建图像。Aiming at the ultrasonic CT reconstruction problem, a maximum likelihood expectation maximization algorithm based on Gaussian model is proposed. And a non-minimization optimization method is presented to select proper initial values. Gaussian model is more suitable for the measured time information than Poisson model. Therefore the new maximum likelihood expectation maximization is superior to the original one. The non- minimization optimization method proposed in this paper can reduce the iteration times, and improve both reconstruction quality and computing efficiency. In order to validate the correctness of the proposed method, a 3D temperature reconstruction simulation is carried out. The results show that the improved maximum likelihood expectation maximization algorithm lowers the average error, and reconstruction images with better accuracy can be obtained.

关 键 词：超声波CT 重建算法 温度场 TOF 最大似然期望最大化方法 非最小最优化 

分 类 号：TN98[电子电信—信息与通信工程] TP391.7[自动化与计算机技术—计算机应用技术]