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

Shu ZamaTomoyuki FujiokaEmi YamagaKazunori Kubota Mio 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
ultrasound guided
contrast enhanced ultrasound
quality improvement
machine learning
computed tomography
risk assessment
medical students