Soleimani Manuchehr, Gómez-Laberge Camille, Adler Andy
William Lee Innovation Centre, School of Materials, University of Manchester, Manchester, UK.
Physiol Meas. 2006 May;27(5):S103-13. doi: 10.1088/0967-3334/27/5/S09. Epub 2006 Apr 18.
Electrical impedance tomography (EIT) attempts to reconstruct the internal impedance distribution in a medium from electrical measurements at electrodes on the medium surface. One key difficulty with EIT measurements is due to the position uncertainty of the electrodes, especially for medical applications, in which the body surface moves during breathing and posture change. In this paper, we develop a new approach which directly reconstructs both electrode movements and internal conductivity changes for difference EIT. The reconstruction problem is formulated in terms of a regularized inverse, using an augmented Jacobian, sensitive to impedance change and electrode movement. A reconstruction prior term is computed to impose a smoothness constraint on both the spatial distribution of impedance change and electrode movement. A one-step regularized imaging algorithm is then implemented based on the augmented Jacobian and smoothness constraint. Images were reconstructed using the algorithm of this paper with data from simulated 2D and 3D conductivity changes and electrode movements, and from saline phantom measurements. Results showed good reconstruction of the actual electrode movements, as well as a dramatic reduction in image artefacts compared to images from the standard algorithm, which did not account for electrode movement.
电阻抗断层成像（EIT）试图根据在介质表面电极处的电学测量来重建介质内部的阻抗分布。EIT测量的一个关键难题是电极位置的不确定性，尤其是在医学应用中，人体表面会在呼吸和姿势改变时发生移动。在本文中，我们开发了一种新方法，该方法直接重建用于差分EIT的电极移动和内部电导率变化。重建问题通过使用对阻抗变化和电极移动敏感的增强雅可比矩阵，以正则化逆的形式来表述。计算一个重建先验项，以对阻抗变化的空间分布和电极移动施加平滑约束。然后基于增强雅可比矩阵和平滑约束实现一步正则化成像算法。使用本文算法，利用模拟的二维和三维电导率变化及电极移动数据以及盐水体模测量数据重建图像。结果表明，实际电极移动得到了很好的重建，并且与未考虑电极移动的标准算法所生成的图像相比，图像伪影显著减少。
