Figure 1.

(a) Framework of the device: In the first step, the system is calibrated using well-defined phantoms. The system is then used to scan the patient’s head and capture scattered signals, which are calibrated against calibration phantom signals. The calibrated data is then processed using a neural network to estimate the contour of the head slice being scanned. Those boundaries are then fed to line crossing, direct mapping, and beamography, which work in an iterative collaborative manner to detect, localize and classify any stroke. In parallel, a tripartite data-driven algorithm is used to map the dielectric properties of all brain tissues. Finally, all the generated images from those algorithms are fed to a fusion algorithm, to give the final image, which shows the location, size, and shape of the stroke in addition to the internal tissue distribution. (b) Main elements of the device: A coupling medium between the antenna array and the head, an antenna array surrounding the head and operating at the low microwave frequency band, an in-line calibration unit for each antenna element, two sets of fixed and flexible cables connecting the antenna array to the multi-port vector network analyzer. (c) The developed device that meets the clinical requirements.