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Clinical Utility of Breast Ultrasound Images Synthesized by a Generative Adversarial Network.

Shu ZamaTomoyuki FujiokaEmi YamagaKazunori KubotaMio MoriLeona KatsutaYuka YashimaArisa SatoMiho KawauchiSubaru HiguchiMasaaki KawanishiToshiyuki IshibaGoshi OdaTsuyoshi NakagawaUkihide Tateishi
Published in: Medicina (Kaunas, Lithuania) (2023)
The DCGAN-synthesized images closely resemble the original ultrasound images in clinical characteristics, suggesting their potential utility in clinical education and training, particularly for enhancing diagnostic skills in breast ultrasound imaging.
Keyphrases
  • deep learning
  • convolutional neural network
  • optical coherence tomography
  • magnetic resonance imaging
  • healthcare
  • contrast enhanced ultrasound
  • machine learning
  • risk assessment
  • human health
  • climate change