DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation
Abstract Deep learning algorithms have recently been developed that utilize patient Airliner Model Kits anatomy and raw imaging information to predict radiation dose, as a means to increase treatment planning efficiency and improve radiotherapy plan quality.Current state-of-the-art techniques rely on convolutional neural networks (CNNs) that use pi