Factorization method and its physical justification in frequency-difference electrical impedance tomography

Bastian Harrach, Jin Keun Seo, Eung Je Woo

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


Time-difference electrical impedance tomography (tdEIT) requires two data sets measured at two different times. The difference between them is utilized to produce images of time-dependent changes in a complex conductivity distribution inside the human body. Frequency-difference EIT (fdEIT) was proposed to image frequency-dependent changes of a complex conductivity distribution. It has potential applications in tumor and stroke imaging since it can visualize an anomaly without requiring any time-reference data obtained in the absence of an anomaly. In this paper, we provide a rigorous analysis for the detectability of an anomaly based on a constructive and quantitative physical correlation between a measured fdEIT data set and an anomaly. From this, we propose a new noniterative frequency-difference anomaly detection method called the factorization method (FM) and elaborate its physical justification. To demonstrate its practical applicability, we performed fdEIT phantom imaging experiments using a multifrequency EIT system. Applying the FM to measured frequency-difference boundary voltage data sets, we could quantitatively evaluate indicator functions inside the imaging domain, of which values at each position reveal presence or absence of an anomaly. We found that the FM successfully localizes anomalies inside an imaging domain with a frequency-dependent complex conductivity distribution. We propose the new FM as an anomaly detection algorithm in fdEIT for potential applications in tumor and stroke imaging.

Original languageEnglish
Article number5491179
Pages (from-to)1918-1926
Number of pages9
JournalIEEE Transactions on Medical Imaging
Issue number11
StatePublished - Nov 2010


  • Anomaly detection
  • complex conductivity
  • electrical impedance tomography (EIT)
  • factorization method
  • weighted frequency difference


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