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Mathematical framework for abdominal electrical impedance tomography to assess fatness

by H. Ammari and H. Kwon and S. Lee and J.K. Seo

(Report number 2016-35)

Abstract
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 human like domain.

Keywords: abdominal electrical impedance tomography, reference-like data, outermost region estimation, sensitivity matrix.

@Techreport{AKLS16_672,
  author = {H. Ammari and H. Kwon and S. Lee and J.K. Seo},
  title = {Mathematical framework for abdominal electrical impedance tomography to assess fatness},
  institution = {Seminar for Applied Mathematics, ETH Z{\"u}rich},
  number = {2016-35},
  address = {Switzerland},
  url = {https://www.sam.math.ethz.ch/sam_reports/reports_final/reports2016/2016-35.pdf },
  year = {2016}
}

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