Glidewell M E, Ng K T
Rincon Research Corporation, Tucson, AZ 85711, USA.
IEEE Trans Med Imaging. 1997 Oct;16(5):572-80. doi: 10.1109/42.640746.
As shown previously for two-dimensional geometries, anisotropy effects should not be ignored in electrical impedance tomography (EIT) and structural information is important for the reconstruction of anisotropic conductivities. Here, we will describe the static reconstruction of an anisotropic conductivity distribution for the more realistic three-dimensional (3-D) case. Boundaries between different conductivity regions are anatomically constrained using magnetic resonance imaging (MRI) data. The values of the conductivities are then determined using gradient-type algorithms in a nonlinear-indirect approach. At each iteration, the forward problem is solved by the finite element method. The approach is used to reconstruct the 3-D conductivity profile of a canine torso. Both computational performance and simulated reconstruction results are presented together with a detailed study on the sensitivity of the prediction error with respect to different parameters. In particular, the use of an intracavity catheter to better extract interior conductivities is demonstrated.
如先前在二维几何结构中所示,在电阻抗断层成像(EIT)中不应忽略各向异性效应,并且结构信息对于重建各向异性电导率很重要。在此,我们将描述更实际的三维(3-D)情况下各向异性电导率分布的静态重建。使用磁共振成像(MRI)数据在解剖学上约束不同电导率区域之间的边界。然后,采用非线性间接方法,通过梯度型算法确定电导率值。在每次迭代中,用有限元法求解正问题。该方法用于重建犬类躯干的三维电导率分布。给出了计算性能和模拟重建结果,并对预测误差相对于不同参数的敏感性进行了详细研究。特别地,展示了使用腔内导管以更好地提取内部电导率的情况。