- Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis
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Yan C, Lin J, Li H, Xu J, Zhang T, Chen H, Woodruff HC, Wu G, Zhang S, Xu Y, Lambin P
- KMID: 2516034
- Korean J Radiol.
- 2021 Jun;22(6):983-993.
- doi: 10.3348/kjr.2020.0988
Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials... -
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