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Fig. 1 | Radiation Oncology

Fig. 1

From: A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images

Fig. 1

Cycle generative adversarial network (CycleGAN) framework (a), and network structure of the generator (b) and discriminator (c). The training model consists of two generators and two discriminators. To train the CycleGAN, the overall network’s performance is enhanced through networks acting bidirectionally with each other. The sCT image is generated by a network that maps images from a source domain (4D-CBCT) to the target domain (4D-MSCT)

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