A novel time-difference electrical impedance tomography algorithm using multi-frequency information

作者：Lu Cao, Haoting Li, Canhua Xu, Meng Dai, Zhenyu Ji, Xuetao Shi, Xiuzhen Dong, Feng Fu, Bin Yang · 发表于：BioMedical Engineering OnLine · 年份：2019 · DOI：10.1186/s12938-019-0703-9 · 被引用次数：25 · 研究领域：Electrical and Bioimpedance Tomography、Microwave Imaging and Scattering Analysis、Numerical methods in inverse problems

BACKGROUND: Electrical impedance tomography (EIT) is a noninvasive, radiation-free, and low-cost imaging modality for monitoring the conductivity distribution inside a patient. Nowadays, time-difference EIT (tdEIT) is used extensively as it has fast imaging speed and can reflect the dynamic changes of diseases, which make it attractive for a number of medical applications. Moreover, modeling errors are compensated to some extent by subtraction of voltage measurements collected before and after the change. However, tissue conductivity varies with frequency and tdEIT does not efficiently exploit multi-frequency information as it only uses measurements associated with a single frequency. METHODS: This paper proposes a tdEIT algorithm that imposes spectral constraints on the framework of the linear least squares problem. Simulation and phantom experiments are conducted to compare the proposed spectral constraints algorithm (SC) with the damped least squares algorithm (DLS), which is a stable tdEIT algorithm used in clinical practice. The condition number and rank of the matrices needing inverses are analyzed, and image quality is evaluated using four indexes. The possibility of multi-tissue imaging and the influence of spectral errors are also explored. RESULTS: Significant performance improvement is achieved by combining multi-frequency and time-difference information. The simulation results show that, in one-step iteration, both algorithms have the same condition number and ran...