Abstract

We proposed a deep learning model with physical constraints to reconstruct the absorption coefficient distribution maps of the lesion inside the breast tissue. Simulation with realistic scenarios and phantom experimental data are used to train the model. We have validated the proposed model on clinical cases and achieved better reconstructed images and a better malignant to benign ratio.

© 2022 The Author(s)