【摘要】 为了提高磁探测电阻抗成像(magnetic detection electrical impedance tomography, MDEIT)中图像分辨率,提出了一种基于图像融合技术提高磁探测电阻抗成像质量的研究。通过利用水平集方法对预处理后的CT图像进行分割,获得结构信息图像;采用CT图像建立模拟肺水肿病变仿真模型,并利用传统灵敏度矩阵算法进行重建,获得MDEIT功能信息图像;利用小波融合算法进行图像融合以获得结构—功能融合图像,并对融合结果进行分析。仿真结果表明,结构信息图像与功能信息图像相融合的图像效果较好。融合图像中重建电导率信息分布更清晰,并且可以实现在实际组织中对病变组织位置和大小精准定位,从而使磁探测电阻抗成像质量得到很大提升,为磁探测电阻抗成像的临床应用奠定了基础。更多还原

【Abstract】 In order to improve the image resolution in magnetic detection electrical impedance imaging, We proposed a research based on image fusion technology to improve the imaging quality of magnetic detection electrical impedance tomography(MDEIT). The pre-processed CT image was segmented by using the level set method to obtain the structural information image. The simulation model of lung edema lesion was established by using the CT image, and the traditional sensitivity matrix algorithm was used to reconstruct the MDEIT function information image. Using wavelet fusion algorithm for image fusion to obtain the structure-function fusion image, after that, the fusion result was analyzed. The simulation results showed that the structure-function fusion image was better than the image with the traditional sensitivity matrix algorithm. The distribution of reconstructed conductivity information in the fusion image is clearer, and the position and size of lesion tissue can be accurately located in the actual tissue, and the imaging quality of MDEIT is greatly improved. Hence, the fusion image can be the foundation of the clinical application of MDEIT.更多还原