Retinal image synthesis from multiple-landmarks input with generative adversarial networks

BACKGROUND: Medical datasets, especially medical images, are often imbalanced due to the different incidences of various diseases. To address this problem, many methods have been proposed to synthesize medical images using generative adversarial networks (GANs) to enlarge training datasets for facil...

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Detalles Bibliográficos
Autores principales: Yu, Zekuan, Xiang, Qing, Meng, Jiahao, Kou, Caixia, Ren, Qiushi, Lu, Yanye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528202/
https://www.ncbi.nlm.nih.gov/pubmed/31113438
http://dx.doi.org/10.1186/s12938-019-0682-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6528202/
https://www.ncbi.nlm.nih.gov/pubmed/31113438
http://dx.doi.org/10.1186/s12938-019-0682-x

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