一种改进的加权频差电阻抗成像算法

An improved weighted frequency differential electrical impedance tomography algorithm

传统加权频差电阻抗成像算法对成像数据采用单加权频差的处理方式,针对权值设置问题采用双加权方法进行权值优化,使背景区域归一化。传统加权频差成像算法采用敏感矩阵数据作为先验信息,在成像结果中存在较多伪影。针对成像结果的伪影问题,对先验信息矩阵进行改进。实验结果表明,优化后的加权频差算法能够从理论上解释其去伪影性能,并且减少了成像中存在的伪影。将实部成像数据与虚部成像数据融合后进行模值成像,进一步提高了成像质量。因此,改进的加权频差算法是一种有效的准静态电阻抗成像算法。

The traditional weighted frequency difference electrical impedance tomography（ EIT） algorithm adopts frequency difference process method of single weight value to process the imaging data. Aiming at the weight setting problem,weight value is optimized based on double weighting method,so that the background area is normalized. The traditional weighted frequency difference EIT algorithm uses the sensitive matrix data as priori information,and there are many artifacts in the imaging results. So we improve the priori information matrix to reduce the artifact. The results indicate that the optimized weighted frequency difference EIT algorithm can theoretically explain its artifact performance and reduce the artifacts in the imaging. In order to further improve the image quality,the real image data and imaginary imaging data are used.Therefore,the improved weighted frequency difference EIT algorithm is an effective quasi-static EIT algorithm.