RESUMEN
Microwave breast imaging has seen significant developments in recent years, including new clinical trials and formation of a number of spin-out companies. Although many algorithms for microwave breast imaging have been developed, there are significant challenges in translating these algorithms to the clinic. For example, movement due to patient breathing can affect the scan, and both the breast and breast abnormalities vary significantly from patient to patient. As breast density is a known independent risk factor for cancer and cancerous tumours have different shapes and margins to benign tumours, the effect of interpatient variance on the microwave image is important. This work analyses the effect on image quality of tumour shape, size and breast density. Using the diverse and representative BRIGID experimental dataset, images of a variety of tumours are compared to images without tumours present. This work suggests that it is difficult to distinguish images with and without tumours present using existing metrics.