Kim Bong Seok, Kim Kyung Youn, Kao Tzu-Jen, Newell Jonathan C, Isaacson David, Saulnier Gary J
Department of Electrical and Electronic Engineering, Cheju National University, Cheju 690-756, Korea.
Physiol Meas. 2006 May;27(5):S81-91. doi: 10.1088/0967-3334/27/5/S07. Epub 2006 Apr 18.
A dynamic complex impedance imaging technique is developed with the aid of the linearized Kalman filter (LKF) for real-time reconstruction of the human chest. The forward problem is solved by an analytical method based on the separation of variables and Fourier series. The inverse problem is treated as a state estimation problem. The nonlinear measurement equation is linearized about the best homogeneous impedivity value as an initial guess, and the impedivity distribution is estimated with the aid of the Kalman estimator. The Kalman gain matrix is pre-computed and stored off-line to minimize the on-line computational time. Simulation and phantom experiment are reported to illustrate the reconstruction performances in the sense of spatio-temporal resolution in a simplified geometry of the human chest.
借助线性化卡尔曼滤波器（LKF）开发了一种动态复阻抗成像技术，用于人体胸部的实时重建。正向问题通过基于变量分离和傅里叶级数的解析方法求解。逆问题被视为一个状态估计问题。非线性测量方程围绕最佳均匀阻抗值作为初始猜测进行线性化，并借助卡尔曼估计器估计阻抗分布。卡尔曼增益矩阵离线预先计算并存储，以最小化在线计算时间。报告了模拟和体模实验，以说明在简化的人体胸部几何结构中，在时空分辨率方面的重建性能。
