Image Improvement Through Metamaterial Technology for Brain Stroke Detection

In this paper we investigate the capabilities of metamaterials technology to enhance the quality of reconstructed images for the problem of brain stroke detection. We integrate the metamaterial in our headband system for brain imaging in CST, and evaluate the reconstructed images of the head model that is placed inside the microwave tomographic head system for the cases with and without the incorporated metamaterial. For image reconstruction we apply the distorted Born iterative method (DBIM) combined with two-step iterative shrinkage/thresholding (TwIST) algorithm. Our results indicate that the use of our metamaterial can increase the signal difference due to the presence of a blood target, which translates into more accurate reconstructions of the target.