Clutter rejection techniques for microwave head imaging

Microwave head imaging is a promising technique for brain injury detection. In that technique, electromagnetic waves are sent into the head by an antenna array surrounding the head and the scattered signals are processed to form an image for brain injury detection purposes. Strong wave reflections from the outer layers of the head and their overlapping with target´s signals can cause a strong clutter in the received signal. This clutter can adversely affect the accuracy of reconstructed image by masking the target response. To that end, different clutter removal techniques, including average subtraction, differential approach, spatial filtering, and entropy-based filtering are investigated in this paper. Those methods are tested in a simulation environment with a realistic head model surrounded by an 8-element antenna array. The obtained results are assessed by performance metrics to compare the ability of the investigated methods in cancelling the clutter from the received signals of microwave head imaging system.