Mathematical framework for abdominal electrical impedance tomography to assess fatness

Habib Ammari, Hyeuknam Kwon, Seungri Lee, Jin Keun Seo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


This paper presents a static electrical impedance tomography (EIT) technique that evaluates abdominal obesity by estimating the thickness of subcutaneous fat. EIT has a fundamental drawback for absolute admittivity imaging because of its lack of reference data for handling the forward modeling errors. To reduce the effect of boundary geometry errors in imaging abdominal fat, we develop a depth-based reconstruction method that uses a specially chosen current pattern to construct reference-like data, which are then used to identify the border between subcutaneous fat and muscle. The performance of the proposed method is demonstrated by numerical simulations using 32-channel EIT system and a humanlike domain.

Original languageEnglish
Pages (from-to)900-919
Number of pages20
JournalSIAM Journal on Imaging Sciences
Issue number2
Publication statusPublished - 2017

Bibliographical note

Publisher Copyright:
© 2017 Society for Industrial and Applied Mathematics.

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Applied Mathematics


Dive into the research topics of 'Mathematical framework for abdominal electrical impedance tomography to assess fatness'. Together they form a unique fingerprint.

Cite this