Quantitative analysis of shape change in Electrical Impedance Tomography (EIT)

Sungho Oh, Te Tang, Rosalind Sadleir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


Electrical Impedance Tomography (EIT) reconstruction is an ill-posed inverse problem, meaning that small amounts of noise or model errors can cause larger artifacts in reconstructed images. One of the largest sources of error is shape change of the imaged object with respect to a reference condition. Systematic shape change artefacts occur in static imaging due to inaccurate assumption of object. Regular shape changes can occur during a time series measurement, such as during the respiratory cycle. We modeled simplified boundary shape changes between circular and elliptic profiles in 2D using the Joukowski transformation. We compared truncated Singular Value Decomposition (tSVD) and Tikhonov regularized reconstruction methods with respect to this shape change in terms of its effect on image quality and Quantity Index (QI) using a single anomaly at various locations within the image plane. During our investigation, we defined a new criterion to choose a suitable regularization parameter for use in quantitative image analysis. The results show that QI is stable over a large range of elliptic distortions, even though quality is not similarly well preserved.

Original languageEnglish (US)
Title of host publication13th International Conference on Electrical Bioimpedance and the 8th Conference on Electrical Impedance Tomography 2007, ICEBI 2007
PublisherSpringer Verlag
Number of pages4
ISBN (Print)9783540738404
StatePublished - 2007
Externally publishedYes

Publication series

NameIFMBE Proceedings
Volume17 IFMBE
ISSN (Print)1680-0737


  • Electrical impedance tomography
  • Quantity index
  • Shape change
  • Tikhonov regularization
  • Truncated singular value decomposition

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering


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