Compressive sensing for stroke detection in microwave-based head imaging

The theory of compressive sensing (CS) provides a method to recover an unknown sparse signal (data) from limited measurements by solving a constrained convex optimization problem. This method has been used in far-field radar imaging applications such as SAR imaging. However, for microwave medical imaging (head imaging or breast imaging), CS technique is seldom investigated. In this paper, a microwave-based head imaging method based on compressive sensing is presented. Compared with the traditional microwave head imaging algorithm (in which 16 antennas were used), only 4 antennas are used in the presented method and the results from CS technique are compared with the conventional confocal algorithm for head imaging. The results show that the target inside the head is properly recovered by using CS, with a significant reduction in the number of used antennas.