Improving image quality and lung nodule detection for low-dose chest CT by using generative adversarial network reconstruction.

The GAN-trained model, which learned the residual between SDCT and LDCT images, reduced image noise and increased the lung nodule detectability by radiologists on chest LDCT. This demonstrates the potential for clinical benefit.