一种混合变差肺部电阻抗成像算法研究

采用混合变差算法进行图像重建既能保持重构结果的连续性又可保持图像重建过程中的非连续性.建立基于有限元方法的二维EIT肺部模型，对模型进行离散，定义模型和各离散对象的物理特性，施加边界条件，计算边界电压，进行正问题仿真，确定算法的目标函数，进行图像重建并对混合变差算法的性能进行评估.在合适的权重值条件下采用混合变差算法重建的图像的结构相似度比采用吉洪诺夫算法和总变差算法重建的图像的结构相似度在无噪声时分别提高了约5.1%和9%，在含噪声时分别提高了约2.7%和6.3%.既可用于仿真研究与实验中，也可用于临床实测数据的图像重建.

An Image Algorithm Based on Mixture Variation for the Pulmonary Electrical Impedance Tomography

Adopting a mixture variation algorithm for reconstructing the image can not only maintain the continuity of the reconstructed results, but also keep the discontinuity during the process. A two-dimensional numerical model on EIT was established based on the finite element method. To optimize the model, we discretized the numerical model, defined the physical characteristics of the model and discrete objects, imposed the boundary condition, calculated the boundary voltage, simulated the forward problems and determined the objective function of the algorithm. Finally, we carried out the image reconstruction and evaluated the performance of the mixture variation algorithm. The structural similarity of the image were improved by about 2% and 2.9%, and the reconstruction speed were increased by about 2.4% and 2.6% respectively, after reconstruction by the mixture variation algorithm under the appropriate weight value compared with that after reconstructed by the Tikhonov algorithm and the total variation algorithm. The mixture variation algorithm can be both used in the image reconstruction of clinical measured data and in the simulation researches and experiments.