Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT

J. Jang, J. K. Seo

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

Original languageEnglish
Article number1179
Pages (from-to)1179-1192
Number of pages14
JournalPhysiological measurement
Volume36
Issue number6
DOIs
Publication statusPublished - 2015 Jun 1

Fingerprint

Acoustic impedance
Tomography
Electric Impedance
Imaging techniques
Skull
Computer simulation
Stroke
Head
Experiments

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Physiology
  • Biomedical Engineering
  • Physiology (medical)

Cite this

@article{7044023f88bf4e4c9ccab69d4af457ad,
title = "Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT",
abstract = "This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.",
author = "J. Jang and Seo, {J. K.}",
year = "2015",
month = "6",
day = "1",
doi = "10.1088/0967-3334/36/6/1179",
language = "English",
volume = "36",
pages = "1179--1192",
journal = "Physiological Measurement",
issn = "0967-3334",
publisher = "IOP Publishing Ltd.",
number = "6",

}

Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT. / Jang, J.; Seo, J. K.

In: Physiological measurement, Vol. 36, No. 6, 1179, 01.06.2015, p. 1179-1192.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT

AU - Jang, J.

AU - Seo, J. K.

PY - 2015/6/1

Y1 - 2015/6/1

N2 - This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

AB - This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

UR - http://www.scopus.com/inward/record.url?scp=84930641520&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84930641520&partnerID=8YFLogxK

U2 - 10.1088/0967-3334/36/6/1179

DO - 10.1088/0967-3334/36/6/1179

M3 - Article

C2 - 26008619

AN - SCOPUS:84930641520

VL - 36

SP - 1179

EP - 1192

JO - Physiological Measurement

JF - Physiological Measurement

SN - 0967-3334

IS - 6

M1 - 1179

ER -