Behkami Saber, Frounchi Javad, Ghaderi Pakdel Firouz, Stieglitz Thomas
Microelectronic and Microsensor Laboratory, Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Tabriz University, Tabriz, East Azerbaijan, Iran.
Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Tabriz University, Tabriz, East Azerbaijan, Iran.
Biomed Tech (Berl). 2018 Mar 28;63(2):151-161. doi: 10.1515/bmt-2016-0089.
The electrode structure in micro-electrical impedance tomography (MEIT) highly influences the measurement sensitivity and therefore the reconstructed image quality. Hence, optimizing the electrode structure leads to the improvement of image quality in the reconstruction procedure. Although there have been many investigations on electrical impedance tomography (EIT) electrodes, there is no comprehensive study on their influence on images of the peripheral nerve. In this paper, we present a simulation method to study the effects of the electrode structure in the density measurement system of the peripheral nerve based on MEIT. The influence of the electrode structure such as dimensions, material and the number of electrodes and also the recognition feature of different radii of fascicle and different locations of fascicles has been studied. Data were reconstructed from the real and imaginary parts of complex conductivity data, respectively. It has been shown that the material of the electrodes had no effect on the reconstructed images, while the dimensions of the electrodes significantly affected the image sensitivity and thus the image quality. An increase in the number of electrodes increased the amount of data and information content. However, as the number of electrodes increased due to the given perimeter of the peripheral nerve, the area of the electrodes was reduced. This reduction affects the reconstructed image quality. The real and imaginary parts of the data were separately reconstructed for each case. Although, in real EIT systems, the reconstructed images using the real part of the signal have a better signal-to-noise ratio (SNR), this study proved that for a density measuring system of the peripheral nerve, the reconstructed images using the imaginary part of the signal had better quality. This simulation study proposes the effects of the electrode size and material and obtained spatial resolution that was high enough to reconstruct fascicles in a peripheral nerve.
微电阻抗断层成像(MEIT)中的电极结构对测量灵敏度有很大影响,进而影响重建图像的质量。因此,优化电极结构可在重建过程中提高图像质量。尽管对电阻抗断层成像(EIT)电极已经有很多研究,但关于其对周围神经图像影响的全面研究尚未见报道。本文提出一种模拟方法,用于研究基于MEIT的周围神经密度测量系统中电极结构的影响。研究了电极结构(如尺寸、材料和电极数量)的影响,以及不同束半径和束位置的识别特征。分别从复电导率数据的实部和虚部重建数据。结果表明,电极材料对重建图像没有影响,而电极尺寸对图像灵敏度和图像质量有显著影响。电极数量的增加会增加数据量和信息含量。然而,由于周围神经周长固定,随着电极数量的增加,电极面积会减小。这种减小会影响重建图像质量。对每种情况分别重建数据的实部和虚部。虽然在实际的EIT系统中,使用信号实部重建的图像具有更好的信噪比(SNR),但本研究证明,对于周围神经密度测量系统,使用信号虚部重建的图像质量更好。该模拟研究提出了电极尺寸和材料的影响,并获得了足以重建周围神经束的高空间分辨率。