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.
Original language | English |
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Pages (from-to) | 2104-2113 |
Number of pages | 10 |
Journal | IEEE Transactions on Medical Imaging |
Volume | 38 |
Issue number | 9 |
Early online date | 25 Jan 2019 |
DOIs | |
Publication status | Published - 1 Sept 2019 |
ASJC Scopus subject areas
- Software
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering
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Manuchehr Soleimani
- Department of Electronic & Electrical Engineering - Professor
- Electronics Materials, Circuits & Systems Research Unit (EMaCS)
- Bath Institute for the Augmented Human
- Centre for Bioengineering & Biomedical Technologies (CBio)
- Centre for Digital, Manufacturing & Design (dMaDe)
Person: Research & Teaching, Core staff, Affiliate staff