Asymptotic analysis of the membrane structure to sensitivity of frequency-difference electrical impedance tomography

被引:15
|
作者
Kim, Sungwhan [1 ]
Lee, Eun Jung [2 ]
Woo, Eung Je [3 ]
Seo, Jin Keun [2 ]
机构
[1] Hanbat Natl Univ, Div Liberal Art, Taejon, South Korea
[2] Yonsei Univ, Dept Computat Sci & Engn, Seoul 120749, South Korea
[3] Kyung Hee Univ, Dept Biomed Engn, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
COMPLEX CONDUCTIVITY; SPHEROIDAL CELLS; EIT SYSTEM; KHU MARK1; IMPLEMENTATION; SPECTROSCOPY; EQUATIONS; DESIGN; MODEL;
D O I
10.1088/0266-5611/28/7/075004
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
There have been numerous studies using multi-frequency electrical impedance tomography to image frequency-dependent admittivity spectra of biological tissues. Considering the fundamental drawback of the static EIT in recovering the absolute admittivity image at a certain frequency, we will focus on a difference imaging method using a currently available EIT system. We are particularly interested in the frequency-difference EIT (fdEIT) in this paper since it may provide spectroscopic admittivity images without requiring a time-reference data. Noting that non-negligible susceptivity values of biological tissues are attributed to thin cell membranes, we analyze the role of the membrane in terms of the sensitivity of the complex voltage data in fdEIT. Such an analysis requires one to study the frequency-dependent behavior of a complex potential in the framework of the elliptic partial differential equation (PDE) with a frequency-dependent complex coefficient representing the admittivity. Due to complicated coupling between the real and imaginary parts of the complex potential, there is little study on the complex elliptic PDE. Although there exist several previous studies using spherical models which allow the potential to be represented as trigonometric series, these approaches are not apt for biological tissues. In this paper, we decouple the real and imaginary parts via a key asymptotic analysis and approximate the real part as a solution of a well-established elliptic PDE with a real coefficient whose value changes with frequency. This more general approach provides a quantitative analysis of the role of the thin membrane in forming a fdEIT image. We perform numerical simulations and phantom experiments on a two-dimensional imaging object containing an anomaly with a thin insulating membrane. The results provide better understanding of the role of the thin membrane in the sensitivity of a multi-frequency current-voltage data.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] ON THE SENSITIVITY METHOD OF RECONSTRUCTION FOR ELECTRICAL-IMPEDANCE TOMOGRAPHY
    GADD, R
    RECORD, PM
    ROLFE, P
    CLINICAL PHYSICS AND PHYSIOLOGICAL MEASUREMENT, 1990, 11 (02): : 180 - 181
  • [32] The Effect of Internal Electrodes on Electrical Impedance Tomography Sensitivity
    Stowe, Symon
    Adler, Andy
    42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 1457 - 1460
  • [33] Sensitivity Matrix for Ultrasound Modulated Electrical Impedance Tomography
    Song, Xizi
    Xu, Yanbin
    Dong, Feng
    2016 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE PROCEEDINGS, 2016, : 585 - 590
  • [34] Numerical simulation and analysis of generalized difference method on triangular networks for electrical impedance tomography
    Li, Jiuping
    Yuan, Yirang
    APPLIED MATHEMATICAL MODELLING, 2009, 33 (05) : 2175 - 2186
  • [35] Determination of internal structure by electrical impedance tomography
    Univ of Newcastle upon Tyne, United Kingdom
    Nondestr Test Eval, 3 (173-181):
  • [36] A novel time-difference electrical impedance tomography algorithm using multi-frequency information
    Cao, Lu
    Li, Haoting
    Xu, Canhua
    Dai, Meng
    Ji, Zhenyu
    Shi, Xuetao
    Dong, Xiuzhen
    Fu, Feng
    Yang, Bin
    BIOMEDICAL ENGINEERING ONLINE, 2019, 18 (1)
  • [37] A novel time-difference electrical impedance tomography algorithm using multi-frequency information
    Lu Cao
    Haoting Li
    Canhua Xu
    Meng Dai
    Zhenyu Ji
    Xuetao Shi
    Xiuzhen Dong
    Feng Fu
    Bin Yang
    BioMedical Engineering OnLine, 18
  • [38] Multi-frequency symmetry difference electrical impedance tomography with machine learning for human stroke diagnosis
    McDermott, Barry
    Elahi, Adnan
    Santorelli, Adam
    O'Halloran, Martin
    Avery, James
    Porter, Emily
    PHYSIOLOGICAL MEASUREMENT, 2020, 41 (07)
  • [39] ON A CALDERON PROBLEM IN FREQUENCY DIFFERENTIAL ELECTRICAL IMPEDANCE TOMOGRAPHY
    Kim, Sungwhan
    Tamasan, Alexandru
    SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 2013, 45 (05) : 2700 - 2709
  • [40] Study on Sweeping Frequency of Electrical Impedance Tomography System
    Wang, Ping
    Wang, Linhong
    Zhang, Li
    Luo, Ciyong
    2008 WORLD AUTOMATION CONGRESS PROCEEDINGS, VOLS 1-3, 2008, : 1792 - +