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...
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Autores principales: | Mingyu Kim, Sungchul Kim, Minjee Kim, Hyun-Jin Bae, Jae-Woo Park, Namkug Kim |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Acceso en línea: | https://doaj.org/article/6c379c130b4846fba9ba730e1fc708a4 |
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