Breast Cancer Imaging at Microwave Frequencies via Neural Networks

Several biomedical imaging modalities are available in the scientific literature for breast cancer diagnosis, each with its own advantages and limitations. In this framework, microwave tomography has gained a certain interest in the last years due to its capability to provide quantitative maps of tissues electric properties in a safe, non-invasive fashion. Furthermore, this imaging modality proved to be cheaper than traditional medical exams. By virtue of the great advantages that artificial intelligence, and more specifically deep learning, has delivered especially in the medical area, this paper proposes a novel procedure for breast cancer imaging by means of microwave radiation. The two-dimensional numerical results reported in this work seem promising and allow to identify and image potential malignancies in the breast.