Abstract
Microwave imaging (MI) is a consistent health monitoring technique that can play a vital role in diagnosing anomalies in the breast. The reliability of biomedical imaging diagnosis is substantially dependent on the imaging algorithm. Widely used delay and sum (DAS)-based diagnosis algorithms suffer from some significant drawbacks. The delay multiply and sum (DMAS) is an improved method and has benefits over DAS in terms of greater contrast and better resolution. However, the main drawback of DMAS is its excessive computational complexity. This paper presents a compressed sensing (CS) approach of iteratively corrected DMAS (CS-ICDMAS) beamforming that reduces the channel calculation and computation time while maintaining image quality. The array setup for acquiring data comprised 16 Vivaldi antennas with a bandwidth of 2.70-11.20 GHz. The power of all the channels was calculated and low power channels were eliminated based on the compression factor. The algorithm involves data-independent techniques that eliminate multiple reflections. This can generate results similar to the uncompressed variants in a significantly lower time which is essential for real-time applications. This paper also investigates the experimental data that prove the enhanced performance of the algorithm.