基于物理模型的静态电阻抗断层成像初步结果

Primary images of static electrical impedance tomography based on physical phantom

目的 研究基于物理模型的静态电阻抗断层成像技术 .方法 使用电阻抗断层成像激励和测量系统 获得物理模型上的测量数据 ,应用正则化校正的 Newton- Raphson算法重构静态阻抗图像 .结果 对几种具有不同电阻率的背景溶液和琼脂目标得到了初步的静态阻抗图像 .背景溶液重构图像的灰度比较均匀 ,重构数值集中在一个较小的范围内 ,且与实际电阻率数值近似成比例关系 ;目标重构图像清晰 ,图像大小与实际大小接近 ,定位基本准确 ,不同电阻率的目标在重构图像中具有不同的数值和灰度 ,对多个目标可以明确区分 ;驱动电流的大小对重构结果的影响很小 .结论 EIT激励和测量系统 所得测量数据的精度基本能满足静态成像的要求 ,正则化校正的重构算法能够有效区分不同电阻率值的目标 。

AIM To study static electrical impedance tomography (EIT) technology based on physical phantom. METHODS Measurement data were obtained from the electrical impedance tomography driving & measuring system Ⅲ. The static impedance images were reconstructed using the regularized Newton Raphson algorithm. RESULTS For several kinds of background solution and agar objects with different resistivity, the primary static EIT images were got. The reconstructed image of background solution had comparative even greyscale. The reconstructed value of background had limited in a narrow scale and proportional to real resistivity. The reconstructed images of agar objects were clear, closed to the real size, and located on the right position. The objects with different resistivity had different value and greyscale in result images. Multiple objects could be distinguished explicitly. The value of driven current had little influence on the result images. CONCLUSION Measurement data sampled by EIT driven & measuring system Ⅲ are precise enough to produce the static impedance images. The regularized reconstructed algorithm is able to distinguish two or more objects with different resistivity and adapt itself to the requirement of static impedance imaging.