Barber D C, Seagar A D
Clin Phys Physiol Meas. 1987;8 Suppl A:47-54. doi: 10.1088/0143-0815/8/4a/006.
Resistance imaging involves the reconstruction of the distribution of electrical resistivity within a conducting object from measurements of the voltages or voltage gradients developed on the boundary of the object while current is flowing within the object. In general, the relationship between the distribution of resistivity in the object and the voltage profile on the object boundary is non-linear and attempts to reconstruct the distribution of resistivity from these profiles usually appear to involve time consuming iterative solutions. If it is assumed that the required resistivity distribution is close to a known reference distribution then it can be shown that there is an approximately linear relationship between the perturbation of the boundary voltage gradient measurements from those of the reference distribution and the logarithm of the resistivity perturbation from the reference distribution. The reconstruction problem then becomes solvable by linear methods. In particular it has proved possible to construct a single-pass back-projection method which can produce images of resistivity from a 16 electrode data collection system. Although the present implementation of this algorithm also assumes that the data is produced from a two-dimensional distribution of resistivity within a circular boundary and that the reference distribution is always uniform it seems capable of reconstructing useful images using data from three dimensional objects, including human subjects.
电阻抗成像涉及在电流在导电物体内部流动时，根据物体边界上产生的电压或电压梯度测量值来重建导电物体内部的电阻率分布。一般来说，物体内部电阻率分布与物体边界上的电压分布之间的关系是非线性的，并且从这些分布重建电阻率分布的尝试通常似乎涉及耗时的迭代解。如果假设所需的电阻率分布接近已知的参考分布，那么可以证明，边界电压梯度测量值相对于参考分布测量值的扰动与电阻率相对于参考分布的扰动的对数之间存在近似线性关系。然后，重建问题就可以通过线性方法解决。特别地，已经证明可以构建一种单次反投影方法，该方法可以从16电极数据采集系统生成电阻率图像。尽管该算法目前的实现还假设数据是由圆形边界内的二维电阻率分布产生的，并且参考分布始终是均匀的，但它似乎能够使用来自三维物体（包括人体）的数据重建有用的图像。
