Regularizing a linearized EIT reconstruction method using a sensitivity-based factorization method

Moon Kyung Choi, Bastian Harrach, Jin Keun Seo

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

For electrical impedance tomography (EIT), most practical reconstruction methods are based on linearizing the underlying non-linear inverse problem. Recently, it has been shown that the linearized problem still contains the exact shape information. However, the stable reconstruction of shape information from measurements of finite accuracy on a limited number of electrodes remains a challenge. In this work, we propose to regularize the standard linearized reconstruction method (LM) for EIT using a non-iterative shape reconstruction method (the factorization method). Our main tool is a discrete-sensitivity-based variant of the factorization method (herein called S-FM) which allows us to formulate and combine both methods in terms of the sensitivity matrix. We give a heuristic motivation for this new method and show numerical examples that indicate its good performance in the localization of anomalies and the alleviation of ringing artifacts.

Original languageEnglish
Pages (from-to)1029-1044
Number of pages16
JournalInverse Problems in Science and Engineering
Volume22
Issue number7
DOIs
Publication statusPublished - 2014 Oct

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Regularizing a linearized EIT reconstruction method using a sensitivity-based factorization method'. Together they form a unique fingerprint.

  • Cite this