TY - JOUR
T1 - Integral formulation of the complete electrode model of electrical impedance tomography
AU - Ma, Erfang
N1 - Publisher Copyright:
© 2020, American Institute of Mathematical Sciences. All rights reserved.
PY - 2020
Y1 - 2020
N2 - We model electrical impedance tomography (EIT) based on the minimum energy principle. It results in a constrained minimization problem in terms of current density. The new formulation is proved to have a unique solution within appropriate function spaces. By characterizing its solution with the Lagrange multiplier method, we relate the new formulation to the so-called shunt model and the complete electrode model (CEM) of EIT. Based on the new formulation, we also propose a new numerical method to solve the forward problem of EIT. The new solver is formulated in terms of current. It was shown to give similar results to that of the traditional finite element method, with simulations on a 2D EIT model.
AB - We model electrical impedance tomography (EIT) based on the minimum energy principle. It results in a constrained minimization problem in terms of current density. The new formulation is proved to have a unique solution within appropriate function spaces. By characterizing its solution with the Lagrange multiplier method, we relate the new formulation to the so-called shunt model and the complete electrode model (CEM) of EIT. Based on the new formulation, we also propose a new numerical method to solve the forward problem of EIT. The new solver is formulated in terms of current. It was shown to give similar results to that of the traditional finite element method, with simulations on a 2D EIT model.
KW - Complete electrode model
KW - Electrical impedance tomography
KW - Forward problem
KW - Minimum energy principle
KW - Shunt model
UR - http://www.scopus.com/inward/record.url?scp=85079641006&partnerID=8YFLogxK
U2 - 10.3934/ipi.2020017
DO - 10.3934/ipi.2020017
M3 - Article
AN - SCOPUS:85079641006
SN - 1930-8337
VL - 14
SP - 385
EP - 398
JO - Inverse Problems and Imaging
JF - Inverse Problems and Imaging
IS - 2
ER -