最大似然-可分离抛物面替代函数双能CT重建算法  

Maximum Likelihood-Separable Paraboloidal Surrogate Function Algorithm for Dual-Energy CT Reconstruction

作　　者：侯晓文 滕月阳[1] 刘瑜珈 康雁[1] 

机构地区：[1]东北大学中荷生物医学与信息工程学院,辽宁沈阳110169

出　　处：《东北大学学报（自然科学版）》2017年第11期1538-1542,共5页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(61372014)

摘　　要：针对重建算法对不同的检测对象需要建立不同的查找表问题,提出了一种基于最大似然-可分离抛物面型替代函数的重建算法.根据双能CT的物理模型和统计模型建立了对数似然函数,并以之为目标函数.根据目标函数的凸性,构造了可分离抛物面型替代函数.实验结果表明,该算法重建所得各能级图像与原始图像的相关系数大于0.983,信噪比大于12 d B,均大于查表法重建结果的相应值,重建图像质量优于查表法.In the reconstruction algorithm,different lookup table problems need to be set up fo r different objects. Analgorithm based on maximum likelihood-separable paraboloidal surrogate function was proposed. Alog - likelihoo d function, as the objective function, was constructed based on the physical model and statistical model of dual-energy CT. Separable paraboloidal surrogate function was constructed according to the convex characteristic of the objective function. The experiment result shows that,for all of the energy levels,the correlation coefficient between the image reconstructed by this method and the original image is greater than 0. 983, and the signal to noise ratio is greater than 12 d B,both are greater than the corresponding values of the result using the look up table algorithm. The quality of image reconstructed by the proposed method was better than the look up table method.

关 键 词：双能CT 最大似然 凸优化 替代函数 重建算法 

分 类 号：TP301.41[自动化与计算机技术—计算机系统结构]