An Image Turing Test on Realistic Gastroscopy Images Generated by Using the Progressive Growing of Generative Adversarial Networks

Generative adversarial networks (GAN) in medicine are valuable techniques for augmenting unbalanced rare data, anomaly detection, and avoiding patient privacy issues. However, there were limits to generating high-quality endoscopic images with various characteristics, such as peristalsis, viewpoints...

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Detalles Bibliográficos
Autores principales: Shin, Keewon, Lee, Jung Su, Lee, Ji Young, Lee, Hyunsu, Kim, Jeongseok, Byeon, Jeong-Sik, Jung, Hwoon-Yong, Kim, Do Hoon, Kim, Namkug
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406771/
https://www.ncbi.nlm.nih.gov/pubmed/36914855
http://dx.doi.org/10.1007/s10278-023-00803-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406771/
https://www.ncbi.nlm.nih.gov/pubmed/36914855
http://dx.doi.org/10.1007/s10278-023-00803-2

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