A Parametric Level Set-based Approach to Difference Imaging in Electrical Impedance Tomography

Research output: Contribution to journalArticleScientificpeer-review


  • Dong Liu
  • Danny Smyl
  • Jianfeng Du

Research units

  • University of Science and Technology of China


This paper presents a novel difference imaging approach based on the recently developed parametric level set (PLS) method for estimating the change in a target conductivity from electrical impedance tomography measurements. As in conventional difference imaging, the reconstruction of conductivity change is based on data sets measured from the surface of a body before and after the change. The key feature of the proposed approach is that the conductivity change to be reconstructed is assumed to be piecewise constant, while the geometry of the anomaly is represented by a shape-based PLS function employing Gaussian radial basis functions (GRBFs). The representation of the PLS function by using GRBF provides flexibility in describing a large class of shapes with fewer unknowns. This feature is advantageous, as it may significantly reduce the overall number of unknowns, improve the condition number of the inverse problem, and enhance the computational efficiency of the technique. To evaluate the proposed PLS-based difference imaging approach, results obtained via simulation, phantom study, and in vivo pig data are studied. We find that the proposed approach tolerates more modeling errors and leads to a significant improvement in image quality compared with the conventional linear approach.


Original languageEnglish
Article number8416750
Pages (from-to)145-155
Number of pages11
JournalIEEE Transactions on Medical Imaging
Issue number1
Publication statusPublished - 1 Jan 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Electrical impedance tomography, parametric level set method, difference imaging, lung imaging, inverse problems, lung imaging, Electrical impedance tomography, difference imaging, parametric level set method, PERMITTIVITY, ERRORS, D-BAR METHOD, RECONSTRUCTION ALGORITHM, ABSOLUTE, SHAPE, SPATIAL PRIOR, CONDUCTIVITY, EIT RECONSTRUCTION, BOUNDARY

ID: 26544473