Literature DB >> 30703015

Capacitively Coupled Electrical Impedance Tomography for Brain Imaging.

Y D Jiang, M Soleimani.   

Abstract

Electrical impedance tomography (EIT) is considered as a potential candidate for brain stroke imaging due to its compactness and potential use in bedside and emergency settings. The electrode-skin contact impedance and low conductivity of skull pose some practical challenges to the EIT head imaging. This paper studies the application of capacitively coupled electrical impedance tomography (CCEIT) in brain imaging for the first time. CCEIT is a new contactless EIT technique which uses voltage excitation without direct contact with the skin, as oppose to directly injecting the current to the skin in EIT. Because the safety issue of a new technique should be strictly treated, simulation work based on a simplified head model was carried out to investigate the safety aspects of CCEIT. By comparing with the standard EIT excited by a typical safe current level used in brain imaging, the safe excitation reference of CCEIT is obtained. This is done by comparing the maximum level of internal electrical field (internal current density) of EIT and that of CCEIT. Simulation results provide useful knowledge of excitation signal level of CCEIT and also show a critical comparison with traditional EIT. Practical experiments were carried out with a 12-electrode CCEIT phantom, saline, and carrot samples. Experimental results show the feasibility and potential of CCEIT for stroke imaging. In this paper, the anomaly diameter resolution is 10 mm (1/18 of the phantom diameter), which indicates that small-volume stroke could be detected. This is achieved by a low excitation voltage of 1 V, showing the possibility of even better performance when higher but yet safe level of excitation voltages is used.

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Year:  2019        PMID: 30703015     DOI: 10.1109/TMI.2019.2895035

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  7 in total

1.  Hybrid method for improving Tikhonov-based reconstruction quality in electrical impedance tomography.

Authors:  Meng Wang; Shuo Zheng; Yanyan Shi; Yajun Lou
Journal:  J Med Imaging (Bellingham)       Date:  2022-10-17

Review 2.  Advances in electrical impedance tomography-based brain imaging.

Authors:  Xi-Yang Ke; Wei Hou; Qi Huang; Xue Hou; Xue-Ying Bao; Wei-Xuan Kong; Cheng-Xiang Li; Yu-Qi Qiu; Si-Yi Hu; Li-Hua Dong
Journal:  Mil Med Res       Date:  2022-02-28

3.  Dynamic Hand Gesture Recognition Using Electrical Impedance Tomography.

Authors:  Xiuyan Li; Jianrui Sun; Qi Wang; Ronghua Zhang; Xiaojie Duan; Yukuan Sun; Jianming Wang
Journal:  Sensors (Basel)       Date:  2022-09-22       Impact factor: 3.847

4.  Arrangement of boundary electrodes for detection of frontal lobe disease with electrical impedance tomography.

Authors:  Yanyan Shi; Zhiwei Tian; Meng Wang; Feng Fu; Yuehui Wu
Journal:  J Med Imaging (Bellingham)       Date:  2021-07-06

5.  A New Label-Free and Contactless Bio-Tomographic Imaging with Miniaturized Capacitively-Coupled Spectroscopy Measurements.

Authors:  Gege Ma; Manuchehr Soleimani
Journal:  Sensors (Basel)       Date:  2020-06-11       Impact factor: 3.576

6.  Anomaly Detection Using Electric Impedance Tomography Based on Real and Imaginary Images.

Authors:  Imam Sapuan; Moh Yasin; Khusnul Ain; Retna Apsari
Journal:  Sensors (Basel)       Date:  2020-03-30       Impact factor: 3.576

7.  An amplitude-based characteristic parameter extraction algorithm for cerebral edema detection based on electromagnetic induction.

Authors:  Jingbo Chen; Gen Li; Huayou Liang; Shuanglin Zhao; Jian Sun; Mingxin Qin
Journal:  Biomed Eng Online       Date:  2021-08-03       Impact factor: 2.819

  7 in total

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