Experimental Validation of the DBIM-TwIST Algorithm for Brain Stroke Detection and Differentiation Using a Multi-Layered Anatomically Complex Head Phantom

We present an experimental validation of the distorted Born iterative method with two-step shrinkage thresholding (DBIM-TwIST) algorithm for problem brain stroke detection and differentiation, using anatomically accurate, multi-layer head phantom. To this end, we have developed a gelatine-based, complex phantom which mimics various tissues also includes target mimicking hemorrhagic or ischemic stroke. simulated model setup CST Microwave Studio then used our imaging to collect numerical measured data, respectively. DBIM-TwIST reconstruct dielectric properties domain both data. Results from simulations showed that are able locate permittivity different targets approximate initial guess. Our results demonstrated potential challenges successful differentiation targets.