Realistic high-resolution lateral cephalometric radiography generated by progressive growing generative adversarial network and quality evaluations

Realistic image generation is valuable in dental medicine, but still challenging for generative adversarial networks (GANs), which require large amounts of data to overcome the training instability. Thus, we generated lateral cephalogram X-ray images using a deep-learning-based progressive growing G...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Mingyu, Kim, Sungchul, Kim, Minjee, Bae, Hyun-Jin, Park, Jae-Woo, Kim, Namkug
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206205/
https://www.ncbi.nlm.nih.gov/pubmed/34131213
http://dx.doi.org/10.1038/s41598-021-91965-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206205/
https://www.ncbi.nlm.nih.gov/pubmed/34131213
http://dx.doi.org/10.1038/s41598-021-91965-y

Ejemplares similares