Perceived realism of high-resolution generative adversarial network–derived synthetic mammograms
D Korkinof, H Harvey, A Heindl, E Karpati… - Radiology: Artificial …, 2020 - pubs.rsna.org
Purpose To explore whether generative adversarial networks (GANs) can enable synthesis
of realistic medical images that are indiscernible from real images, even by domain experts …
of realistic medical images that are indiscernible from real images, even by domain experts …
Perceived Realism of High-Resolution Generative Adversarial Network-derived Synthetic Mammograms.
D Korkinof, H Harvey, A Heindl, E Karpati… - Radiology. Artificial …, 2020 - europepmc.org
Purpose To explore whether generative adversarial networks (GANs) can enable synthesis
of realistic medical images that are indiscernible from real images, even by domain experts …
of realistic medical images that are indiscernible from real images, even by domain experts …
Perceived Realism of High-Resolution Generative Adversarial Network-derived Synthetic Mammograms
D Korkinof, H Harvey, A Heindl… - Radiology. Artificial …, 2020 - pubmed.ncbi.nlm.nih.gov
Purpose To explore whether generative adversarial networks (GANs) can enable synthesis
of realistic medical images that are indiscernible from real images, even by domain experts …
of realistic medical images that are indiscernible from real images, even by domain experts …
[HTML][HTML] Perceived Realism of High-Resolution Generative Adversarial Network–derived Synthetic Mammograms
D Korkinof, H Harvey, A Heindl, E Karpati… - Radiology. Artificial …, 2021 - ncbi.nlm.nih.gov
Purpose To explore whether generative adversarial networks (GANs) can enable synthesis
of realistic medical images that are indiscernible from real images, even by domain experts …
of realistic medical images that are indiscernible from real images, even by domain experts …
[HTML][HTML] Perceived Realism of High-Resolution Generative Adversarial Network–derived Synthetic Mammograms
D Korkinof, H Harvey, A Heindl, E Karpati… - Radiology: Artificial …, 2020 - pubs.rsna.org
Purpose To explore whether generative adversarial networks (GANs) can enable synthesis
of realistic medical images that are indiscernible from real images, even by domain experts …
of realistic medical images that are indiscernible from real images, even by domain experts …