Performance of leading artifact removal algorithms assessed across microwave breast imaging prototype scan configurations

Abstract

Microwave imaging is a promising imaging modality for the detection of early-stage breast cancer. One of the most important signal processing components of microwave radar-based breast imaging is early-stage artifact removal. Several artifact removal algorithms have been reported in the literature. However, the neighbourhood-based skin subtraction and hybrid artifact removal algorithms have shown particularly promising results in different realistic 3D breast phantoms. For the first time in this paper, both algorithms have been evaluated and compared using the scan approaches of the most common microwave breast imaging prototype systems. The tests include 3D numerical as well as experimental breast phantoms scanned with hemispherical, cylindrical and adaptive scanning patterns. The efficacy of both algorithms has been evaluated across a range of appropriate performance metrics.