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Refinement of image quality in panoramic radiography using a generative adversarial network.

Hak-Sun KimEun-Gyu HaAri LeeYoon Joo ChoiKug Jin JeonSang-Sun HanChena Lee
Published in: Dento maxillo facial radiology (2023)
The GAN model developed in this study has the potential to improve panoramic radiographs with degraded image quality, both quantitatively and qualitatively. As the model performs better in refining blurred images, further research is required to identify the most effective methods for handling noisy images.
Keyphrases
  • image quality
  • computed tomography
  • deep learning
  • dual energy
  • convolutional neural network
  • optical coherence tomography
  • magnetic resonance imaging
  • magnetic resonance
  • human health