Quantitative imaging of numerically realistic human head model using microwave tomography

Microwave tomography (MWT) is exploited for the detection of haemorrhagic stroke by using a nonlinear iterative imaging algorithm. An anatomically realistic two-dimensional (2D) head model is simulated using a finite difference time-domain numerical solver. By using an iterative optimisation algorithm based on the Gauss-Newton approach, the head model with an artificially embedded stroke region modelled as blood is successfully reconstructed through a blind reconstruction procedure (i.e. no a priori information about the shape or the dielectric properties of the model is assumed). It is observed that beginning from a homogeneous guess similar to the background material, right after the first iteration the shapes of the layers are clearly distinguished and the values of the dielectric properties converge to the actual values after only 10 iterations.