Image Turing test and its applications on synthetic chest radiographs by using the progressive growing generative adversarial network

The generative adversarial network (GAN) is a promising deep learning method for generating images. We evaluated the generation of highly realistic and high-resolution chest radiographs (CXRs) using progressive growing GAN (PGGAN). We trained two PGGAN models using normal and abnormal CXRs, solely r...

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Detalles Bibliográficos
Autores principales: Jang, Miso, Bae, Hyun-jin, Kim, Minjee, Park, Seo Young, Son, A-yeon, Choi, Se Jin, Choe, Jooae, Choi, Hye Young, Hwang, Hye Jeon, Noh, Han Na, Seo, Joon Beom, Lee, Sang Min, Kim, Namkug
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911730/
https://www.ncbi.nlm.nih.gov/pubmed/36759636
http://dx.doi.org/10.1038/s41598-023-28175-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911730/
https://www.ncbi.nlm.nih.gov/pubmed/36759636
http://dx.doi.org/10.1038/s41598-023-28175-1

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