High fidelity imaging and high performance computing in nonlinear EIT.

We show that nonlinear EIT provides images with well defined characteristics when smoothness of the image is used as a constraint in the reconstruction process. We use the gradient of the logarithm of resistivity as an effective measure of image smoothness, which has the advantage that resistivity and conductivity are treated with equal weight. We suggest that a measure of the fidelity of the image to the object requires the explicit definition and application of such a constraint. The algorithm is applied to the simulation of intra-ventricular haemorrhaging (IVH) in a simple head model. The results indicate that a 5% increase in the blood content of the ventricles would be easily detectable with the noise performance of contemporary instrumentation. The possible implementation of the algorithm in real time via high performance computing is discussed.