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      Simultaneous Imaging of Bio- and Non-Conductive Targets by Combining Frequency and Time Difference Imaging Methods in Electrical Impedance Tomography

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          Abstract

          As a promising medical imaging modality, electrical impedance tomography (EIT) can image the electrical properties within a region of interest using electrical measurements applied at electrodes on the region boundary. This paper proposes to combine frequency and time difference imaging methods in EIT to simultaneously image bio- and non-conductive targets, where the image fusion is accomplished by applying a wavelet-based technique. To enable image fusion, both time and frequency difference imaging methods are investigated regarding the reconstruction of bio- or non-conductive inclusions in the target region at varied excitation frequencies, indicating that none of those two methods can tackle with the scenarios where both bio- and non-conductive inclusions exist. This dilemma can be resolved by fusing the time difference (td) and appropriate frequency difference (fd) EIT images since they are complementary to each other. Through simulation and in vitro experiment, it is demonstrated that the proposed fusion method can reasonably reconstruct both the bio- and non-conductive inclusions within the lung models established to simulate the ventilation process, which is expected to be beneficial for the diagnosis of lung-tissue related diseases by EIT.

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          Most cited references33

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          The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz.

          Three experimental techniques based on automatic swept-frequency network and impedance analysers were used to measure the dielectric properties of tissue in the frequency range 10 Hz to 20 GHz. The technique used in conjunction with the impedance analyser is described. Results are given for a number of human and animal tissues, at body temperature, across the frequency range, demonstrating that good agreement was achieved between measurements using the three pieces of equipment. Moreover, the measured values fall well within the body of corresponding literature data.
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            Pixel-level image fusion: A survey of the state of the art

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              The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues.

              A parametric model was developed to describe the variation of dielectric properties of tissues as a function of frequency. The experimental spectrum from 10 Hz to 100 GHz was modelled with four dispersion regions. The development of the model was based on recently acquired data, complemented by data surveyed from the literature. The purpose is to enable the prediction of dielectric data that are in line with those contained in the vast body of literature on the subject. The analysis was carried out on a Microsoft Excel spreadsheet. Parameters are given for 17 tissue types.
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                Author and article information

                Journal
                Biosensors (Basel)
                Biosensors (Basel)
                biosensors
                Biosensors
                MDPI
                2079-6374
                31 May 2021
                June 2021
                : 11
                : 6
                : 176
                Affiliations
                [1 ]School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; bxbuaabj@ 123456buaa.edu.cn (X.B.); weijinzhao@ 123456buaa.edu.cn (J.W.); xubai11@ 123456163.com (X.B.); sunsj@ 123456buaa.edu.cn (S.S.)
                [2 ]Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China
                [3 ]College of Engineering, China Agricultural University, Beijing 100083, China; wenbin.tian@ 123456hotmail.com
                Author notes
                [* ]Correspondence: liudun@ 123456buaa.edu.cn
                Author information
                https://orcid.org/0000-0002-8121-9391
                Article
                biosensors-11-00176
                10.3390/bios11060176
                8226516
                34072777
                f6b9b60e-b766-438a-9e38-9e7e4dbf3f75
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 20 April 2021
                : 28 May 2021
                Categories
                Article

                electrical impedance tomography,frequency difference,time difference,lung imaging

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