Microwave Breast Imaging Via Deep Learning
Michele Ambrosanio, Maria Maddalena Autorino, Stefano Franceschini, Fabio Baselice, Vito Pascazio
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The proposed paper investigates the use of deep learning schemes to perform fast quantitative microwave imaging in the framework of breast cancer detection to support medical decisions. Nowadays, Conventional approaches have some drawbacks related to patient’s safety, processing time and cost, and in this framework microwave imaging can represent a valid alternative due to the use of non-ionising radiations and its affordability. In this framework, deep learning can considerably speed up the inversion procedure, making three-dimensional imaging more convenient and manageable for future perspective.