Generative Adversarial Networks
DU-GAN
Introduced by Huang et al. in DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT DenoisingDU-GAN is a generative adversarial network for LDCT denoising in medical imaging. The generator produces denoised LDCT images, and two independent branches with U-Net based discriminators perform at the image and gradient domains. The U-Net based discriminator provides both global structure and local per-pixel feedback to the generator. Furthermore, the image discriminator encourages the generator to produce photo-realistic CT images while the gradient discriminator is utilized for better edge and alleviating streak artifacts caused by photon starvation.
Source: DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising
Papers
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U-Net
