Scaled Coherence Factor Based Delay Multiply and Sum Beamforming Algorithm in Microwave Imaging

ABSTRACT Microwave imaging is a highly promising modality for the early detection of breast cancer. A multitude of image reconstruction algorithms have been devised. Previous methods utilized the coherence factor (CF) to enhance image quality. However, CF‐based methods often oversuppress the desired signals and introduce image artifacts when the signal‐to‐noise ratio is low. This study introduces a scaled coherence factor‐based delay multiply and sum (DMAS) Beamforming technique to achieve good noise suppression while maintaining robustness. The performance of this method was evaluated using datasets derived from an experimental breast phantom. The results show that the proposed method achieves improvements of signal‐to‐clutter ratio by 26%, signal‐to‐mean ratio by 7%, full‐width at half‐maximum by 8%, and localization error by 51% compared to the CF‐DMAS method. The suggested microwave imaging approach for breast cancer detection provides high resolution, contrast, and localization accuracy along with low computational complexity.