信噪比对不同EIT图像重建算法的影响研究及评价

doi:10.3969/j.issn.0258-8021.2012.06.002

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摘要探索不同位置单目标和多目标电阻抗断层成像（EIT）中，信噪比对不同EIT图像重建算法应用效果的影响。针对16电极系统，通过仿真获取EIT场域理想边界电压作为理想EIT系统的采集信号，对理想系统所有通道采集的数据整体添加高斯白噪声，模拟信噪比为40、60、80 dB的EIT检测系统的测量电压。采用等位线反投影(LBP)、基于Newton-Raphson算法的Tikhonov正则化(NR-Tikhonov) 和Tikhonov-Noser组合正则化（NR Tikhonov-Noser）、Landweber迭代以及NewtonRaphson 5种算法，重建EIT图像。引入重建误差ER和结构相似度函数SSIM，定量评价成像效果。结果表明，当单目标由场域中心向场域边界移动时，5种算法的SSIM都增大；当目标位置靠近边界但个数增加时，5种算法的ER都增大。LBP和NR Tikhonov-Noser在3种信噪比的系统中均可对5种目标模型成像，5种算法中NR Tikhonov-Noser成像质量最好。对场域中心的目标A，NewtonRaphson算法在40 dB信噪比时无法成像，NR Tikhonov、 Landweber在40和60 dB时均不能获得有效图像。在80 dB系统中，LBP成像效果不及另4种算法。不同算法成像对EIT检测系统信噪比的要求不一致，应依据构建的EIT检测系统信噪比指标和具体应用目标择优选取成像算法。NR-TikhonovNoser可作为一般情况下的首选算法，信噪比低于60 dB的系统建议选择LBP，80 dB以上的系统不建议选择LBP。60 dB左右的系统还建议可选择Newton-Raphson算法成像。

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	邓娟¹陈素华¹沙洪²赵舒²任超世^2*

关键词 ： EIT, 信噪比, 算法, 评价

Abstract：This work explored the application effect of different electrical impedance tomography (EIT) image reconstruction algorithms in the imaging of single target with different positions or multi-targets when using detection system with different signal-to-noise ratio(SNR). Aiming at EIT system with 16 electrodes, ideal boundary voltage of EIT field obtained by simulation was taken as signal acquired by ideal EIT system, gauss white noise was added to the whole data collected by all the channels of ideal system, so as to simulate the measuring voltage collected by EIT detection systems of which SNR are 40 dB, 60 dB and 80 dB. The linear backprojection algorithm (LBP), Tikhonov regularization, the combined Tikhonov-Noser regularization algorithm, the Landweber iterative and Newton-Raphson algorithm were adopted in the image reconstruction. Imaging error function ER and structure similarity degree SSIM were introduced to evaluate the reconstructed images. With the movement of a single target from the center to the edge of the field, the value of SSIM of all the 5 algorithms increased. For the targets near to the field edge, the value of ER of all the 5 algorithms increased with the increase of targets number. Both LBP and the combined Tikhonov-Noser regularization algorithm successfully produced images for all the 5 targets supposed in this study under the three EIT systems with different SNR. Of all the 5 algorithms, Tikhonov-Noser regularization algorithm obtained the best image reconstruction quality. For the target A near to the field centre, Newton-Raphson algorithm was unable to image when the SNR was 40 dB, while the SNR which Tikhonov and Landweber algorithms are unable to image was from 40 dB to 60 dB. When SNR was 80 dB, image reconstruction quality of LBP was the lowest of all the 5 algorithms. Different algorithms had different requirements to SNR of EIT detection system, the index SNR should be designed according to concrete application target and algorithms adopted when EIT detection system is constructed. Generally, the combined Tikhonov-Noser regularization algorithm was preferred. When the SNR of the system under 60 dB, LBP was advised and it should be abandoned when SNR was over 80 dB. Newton-Raphson is advised when the SNR was about 60 dB.

Key words： electrical impedance tomography（EIT） signal-to-noise ratio algorithms evaluation

基金资助:江西省自然科学基金青年基金（20122BAB211020）

引用本文:

邓娟¹陈素华¹沙洪²赵舒²任超世^{2*
. 信噪比对不同EIT图像重建算法的影响研究及评价[J]. 中国生物医学工程学报, 2012, 31(6): 807-815.

DENG Juan¹CHEN Suhua¹SHA Hong²ZHAO Shu²REN Chaoshi^{2
. Impact Study and Evaluation of SNR on Different Electrical Impedance Tomography Reconstruction Algorithms. journal1, 2012, 31(6): 807-815.}}

链接本文:

http://cjbme.csbme.org/CN/10.3969/j.issn.0258-8021.2012.06.002 或 http://cjbme.csbme.org/CN/Y2012/V31/I6/807

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