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 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 neu...
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| Principais autores: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2020-07-01
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| coleção: | Scientific Reports |
| Acesso em linha: | https://doi.org/10.1038/s41598-020-68062-7 |
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