Anomaly depth detection in trans-admittance mammography: A formula independent of anomaly size or admittivity contrast

Tingting Zhang, Eunjung Lee, Jin Keun Seo

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Trans-admittance mammography (TAM) is a bioimpedance technique for breast cancer detection. It is based on the comparison of tissue conductivity: cancerous tissue is identified by its higher conductivity in comparison with the surrounding normal tissue. In TAM, the breast is compressed between two electrical plates (in a similar architecture to x-ray mammography). The bottom plate has many sensing point electrodes that provide two-dimensional images (trans-admittance maps) that are induced by voltage differences between the two plates. Multi-frequency admittance data (Neumann data) are measured over the range 50 Hz-500 kHz. TAM aims to determine the location and size of any anomaly from the multi-frequency admittance data. Various anomaly detection algorithms can be used to process TAM data to determine the transverse positions of anomalies. However, existing methods cannot reliably determine the depth or size of an anomaly. Breast cancer detection using TAM would be improved if the depth or size of an anomaly could also be estimated, properties that are independent of the admittivity contrast. A formula is proposed here that can estimate the depth of an anomaly independent of its size and the admittivity contrast. This depth estimation can also be used to derive an estimation of the size of the anomaly. The proposed estimations are verified rigorously under a simplified model. Numerical simulation shows that the proposed method also works well in general settings.

Original languageEnglish
Article number045003
JournalInverse Problems
Volume30
Issue number4
DOIs
Publication statusPublished - 2014 Jan 1

Fingerprint

Mammography
Anomaly
Tissue
Breast Cancer
Conductivity
Depth Estimation
Anomaly Detection
Electrode
Sensing
Transverse
Voltage
X rays
Numerical Simulation
Electrodes
Computer simulation
Electric potential
Estimate
Range of data

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Signal Processing
  • Mathematical Physics
  • Computer Science Applications
  • Applied Mathematics

Cite this

@article{099c80d034a84e0e86ffc1160f2588bb,
title = "Anomaly depth detection in trans-admittance mammography: A formula independent of anomaly size or admittivity contrast",
abstract = "Trans-admittance mammography (TAM) is a bioimpedance technique for breast cancer detection. It is based on the comparison of tissue conductivity: cancerous tissue is identified by its higher conductivity in comparison with the surrounding normal tissue. In TAM, the breast is compressed between two electrical plates (in a similar architecture to x-ray mammography). The bottom plate has many sensing point electrodes that provide two-dimensional images (trans-admittance maps) that are induced by voltage differences between the two plates. Multi-frequency admittance data (Neumann data) are measured over the range 50 Hz-500 kHz. TAM aims to determine the location and size of any anomaly from the multi-frequency admittance data. Various anomaly detection algorithms can be used to process TAM data to determine the transverse positions of anomalies. However, existing methods cannot reliably determine the depth or size of an anomaly. Breast cancer detection using TAM would be improved if the depth or size of an anomaly could also be estimated, properties that are independent of the admittivity contrast. A formula is proposed here that can estimate the depth of an anomaly independent of its size and the admittivity contrast. This depth estimation can also be used to derive an estimation of the size of the anomaly. The proposed estimations are verified rigorously under a simplified model. Numerical simulation shows that the proposed method also works well in general settings.",
author = "Tingting Zhang and Eunjung Lee and Seo, {Jin Keun}",
year = "2014",
month = "1",
day = "1",
doi = "10.1088/0266-5611/30/4/045003",
language = "English",
volume = "30",
journal = "Inverse Problems",
issn = "0266-5611",
publisher = "IOP Publishing Ltd.",
number = "4",

}

Anomaly depth detection in trans-admittance mammography : A formula independent of anomaly size or admittivity contrast. / Zhang, Tingting; Lee, Eunjung; Seo, Jin Keun.

In: Inverse Problems, Vol. 30, No. 4, 045003, 01.01.2014.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Anomaly depth detection in trans-admittance mammography

T2 - A formula independent of anomaly size or admittivity contrast

AU - Zhang, Tingting

AU - Lee, Eunjung

AU - Seo, Jin Keun

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Trans-admittance mammography (TAM) is a bioimpedance technique for breast cancer detection. It is based on the comparison of tissue conductivity: cancerous tissue is identified by its higher conductivity in comparison with the surrounding normal tissue. In TAM, the breast is compressed between two electrical plates (in a similar architecture to x-ray mammography). The bottom plate has many sensing point electrodes that provide two-dimensional images (trans-admittance maps) that are induced by voltage differences between the two plates. Multi-frequency admittance data (Neumann data) are measured over the range 50 Hz-500 kHz. TAM aims to determine the location and size of any anomaly from the multi-frequency admittance data. Various anomaly detection algorithms can be used to process TAM data to determine the transverse positions of anomalies. However, existing methods cannot reliably determine the depth or size of an anomaly. Breast cancer detection using TAM would be improved if the depth or size of an anomaly could also be estimated, properties that are independent of the admittivity contrast. A formula is proposed here that can estimate the depth of an anomaly independent of its size and the admittivity contrast. This depth estimation can also be used to derive an estimation of the size of the anomaly. The proposed estimations are verified rigorously under a simplified model. Numerical simulation shows that the proposed method also works well in general settings.

AB - Trans-admittance mammography (TAM) is a bioimpedance technique for breast cancer detection. It is based on the comparison of tissue conductivity: cancerous tissue is identified by its higher conductivity in comparison with the surrounding normal tissue. In TAM, the breast is compressed between two electrical plates (in a similar architecture to x-ray mammography). The bottom plate has many sensing point electrodes that provide two-dimensional images (trans-admittance maps) that are induced by voltage differences between the two plates. Multi-frequency admittance data (Neumann data) are measured over the range 50 Hz-500 kHz. TAM aims to determine the location and size of any anomaly from the multi-frequency admittance data. Various anomaly detection algorithms can be used to process TAM data to determine the transverse positions of anomalies. However, existing methods cannot reliably determine the depth or size of an anomaly. Breast cancer detection using TAM would be improved if the depth or size of an anomaly could also be estimated, properties that are independent of the admittivity contrast. A formula is proposed here that can estimate the depth of an anomaly independent of its size and the admittivity contrast. This depth estimation can also be used to derive an estimation of the size of the anomaly. The proposed estimations are verified rigorously under a simplified model. Numerical simulation shows that the proposed method also works well in general settings.

UR - http://www.scopus.com/inward/record.url?scp=84897425928&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897425928&partnerID=8YFLogxK

U2 - 10.1088/0266-5611/30/4/045003

DO - 10.1088/0266-5611/30/4/045003

M3 - Article

AN - SCOPUS:84897425928

VL - 30

JO - Inverse Problems

JF - Inverse Problems

SN - 0266-5611

IS - 4

M1 - 045003

ER -