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Induced current electrical impedance tomography system: experimental results and numerical simulations

机译:感应电流电阻抗层析成像系统:实验结果和数值模拟

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In electrical impedance tomography (EIT), measurements of developed surface potentials due to applied currents are used for the reconstruction of the conductivity distribution. Practical implementation of EIT systems is known to be problematic due to the high sensitivity to noise of such systems, leading to a poor imaging quality. In the present study, the performance of an induced current EIT (ICEIT) system, where eddy current is applied using magnetic induction, was studied by comparing the voltage measurements to simulated data, and examining the imaging quality with respect to simulated reconstructions for several phantom configurations. A 3-coil, 32-electrode ICEIT system was built, and an iterative modified Newton–Raphson algorithm was developed for the solution of the inverse problem. The RMS norm between the simulated and the experimental voltages was found to be 0.08 ± 0.05 mV (<3%). Two regularization methods were implemented and compared: the Marquardt regularization and the Laplacian regularization (a bounded second-derivative regularization). While the Laplacian regularization method was found to be preferred for simulated data, it resulted in distinctive spatial artifacts for measured data. The experimental reconstructed images were found to be indicative of the angular positioning of the conductivity perturbations, though the radial sensitivity was low, especially when using the Marquardt regularization method.
机译:在电阻抗断层扫描(EIT)中,由于施加电流而产生的表面电势的测量结果用于重建电导率分布。已知由于这种系统对噪声的高敏感性而导致EIT系统的实际实施存在问题,从而导致较差的成像质量。在本研究中,通过将电压测量值与模拟数据进行比较,并针对几种体模的模拟重建检查成像质量,研究了感应电流EIT(ICEIT)系统的性能,该系统使用磁感应来施加涡流。配置。建立了一个三线圈,32电极的ICEIT系统,并为迭代求解反问题,开发了迭代改进的Newton-Raphson算法。发现仿真电压与实验电压之间的RMS范数为0.08±0.05 mV(<3%)。实施并比较了两种正则化方法:Marquardt正则化和Laplacian正则化(有界二阶导数正则化)。虽然拉普拉斯正则化方法被认为是模拟数据的首选方法,但它却导致了测量数据的独特空间伪影。实验重建的图像被发现可以指示电导率扰动的角度位置,尽管径向灵敏度很低,尤其是在使用Marquardt正则化方法时。

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