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Unsupervised anomaly appraisal of cleft faces using a StyleGAN2-based model adaptation technique
A novel machine learning framework that is able to consistently detect, localize, and measure the severity of human congenital cleft lip anomalies is introduced. The ultimate goal is to fill an important clinical void: to provide an objective and clinically feasible method of gauging baseline facial...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10399833/ https://www.ncbi.nlm.nih.gov/pubmed/37535557 http://dx.doi.org/10.1371/journal.pone.0288228 |