Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, 61600 Brno, Czech Republic.
Sensors (Basel). 2021 Apr 3;21(7):2507. doi: 10.3390/s21072507.
This paper discusses the optimization of domain parameters in electrical impedance tomography-based imaging. Precise image reconstruction requires accurate, well-correlated physical and numerical finite element method (FEM) models; thus, we employed the Nelder-Mead algorithm and a complete electrode model to evaluate the individual parameters, including the initial conductivity, electrode misplacement, and shape deformation. The optimization process was designed to calculate the parameters of the numerical model before the image reconstruction. The models were verified via simulation and experimental measurement with single source current patterns. The impact of the optimization on the above parameters was reflected in the applied image reconstruction process, where the conductivity error dropped by 6.16% and 11.58% in adjacent and opposite driving, respectively. In the shape deformation, the inhomogeneity area ratio increased by 11.0% and 48.9%; the imprecise placement of the 6th electrode was successfully optimized with adjacent driving; the conductivity error dropped by 12.69%; and the inhomogeneity localization exhibited a rise of 66.7%. The opposite driving option produces undesired duality resulting from the measurement pattern. The designed optimization process proved to be suitable for correlating the numerical and the physical models, and it also enabled us to eliminate imaging uncertainties and artifacts.
本文讨论了基于电阻抗成像的域参数优化。精确的图像重建需要准确、良好相关的物理和数值有限元方法 (FEM) 模型；因此，我们采用了 Nelder-Mead 算法和完整的电极模型来评估个体参数，包括初始电导率、电极错位和形状变形。优化过程旨在在图像重建之前计算数值模型的参数。通过单源电流模式的模拟和实验测量对模型进行了验证。优化对上述参数的影响反映在应用的图像重建过程中，相邻和相反驱动时的电导率误差分别降低了 6.16%和 11.58%。在形状变形中，不均匀区域比增加了 11.0%和 48.9%；相邻驱动时成功优化了第 6 个电极的不精确放置，电导率误差降低了 12.69%，不均匀定位的上升了 66.7%。相反的驱动选择会由于测量模式而产生不理想的对偶性。设计的优化过程被证明适合于关联数值和物理模型，并且还能够消除成像不确定性和伪影。
