Realistic high-resolution lateral cephalometric radiography generated by progressive growing generative adversarial network and quality evaluations
Abstract 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...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-06-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-91965-y |