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Conditioning Electrical Impedance Mammography Systems editor version final v2.pdf (1.02 MB)

Conditioning electrical impedance mammography system

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journal contribution
posted on 2023-06-09, 08:31 authored by Ali Zarafshani, Thomas Bach, Chris ChatwinChris Chatwin, Shanshan Tang, Liangzhong Xiang, Bin Zheng
A multi-frequency Electrical Impedance Mammography (EIM) system has been developed to evaluate the conductivity and permittivity spectrums of breast tissues, which aims to improve early detection of breast cancer as a non-invasive, relatively low cost and label-free screening (or pre-screening) method. Multi-frequency EIM systems typically employ current excitations and measure differential potentials from the subject under test. Both the output impedance and system performance (SNR and accuracy) depend on the total output resistance, stray and output capacitances, capacitance at the electrode level, crosstalk at the chip and PCB levels. This makes the system design highly complex due to the impact of the unwanted capacitive effects, which substantially reduce the output impedance of stable current sources and bandwidth of the data that can be acquired. To overcome these difficulties, we present new methods to design a high performance, wide bandwidth EIM system using novel second generation current conveyor operational amplifiers based on a gyrator (OCCII-GIC) combination with different current excitation systems to cancel unwanted capacitive effects from the whole system. We reconstructed tomography images using a planar E-phantom consisting of an RSC circuit model, which represents the resistance of extra-cellular (R), intra-cellular (S) and membrane capacitance (C) of the breast tissues to validate the performance of the system. The experimental results demonstrated that an EIM system with the new design achieved a high output impedance of 10MO at 1MHz to at least 3MO at 3MHz frequency, with an average SNR and modelling accuracy of over 80dB and 99%, respectively.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Measurement

ISSN

0263-2241

Publisher

Elsevier

Volume

116

Page range

38-48

Department affiliated with

  • Engineering and Design Publications

Research groups affiliated with

  • Industrial Informatics and Signal Processing Research Group Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2017-10-31

First Open Access (FOA) Date

2018-11-07

First Compliant Deposit (FCD) Date

2017-10-31

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