Perceived Realism of High-Resolution Generative Adversarial Network–derived Synthetic Mammograms

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. MATERIALS AND METHODS: In this retrospective study, progressive growing GANs were used to synthesize mammograms at a re...

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Vydáno v:Radiol Artif Intell
Hlavní autoři: Korkinof, Dimitrios, Harvey, Hugh, Heindl, Andreas, Karpati, Edith, Williams, Gareth, Rijken, Tobias, Kecskemethy, Peter, Glocker, Ben
Médium: Artigo
Jazyk:Inglês
Vydáno: Radiological Society of North America 2020
Témata:
Original Research
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC8043361/
https://ncbi.nlm.nih.gov/pubmed/33937856
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2020190181
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