Adapting a style based generative adversarial network to create images depicting cleft lip deformity
Abstract Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. We have built a deep learning-based cleft lip generator called CleftGAN designed to produce an almost unlimited num...
Saved in:
Main Authors: | Abdullah Hayajneh, Erchin Serpedin, Mohammad Shaqfeh, Graeme Glass, Mitchell A. Stotland |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-025-86588-6 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Epidemiologic trends of cleft lip and/or palate in Switzerland
by: Joël Beyeler, et al.
Published: (2025-01-01) -
Meta-analysis and systematic review for the genetic basis of cleft lip and palate
by: Wafaa Yahia Alghonemy, et al.
Published: (2025-01-01) -
Assessment of level of knowledge and satisfaction of website about cleft lip and palate
by: Melissa Picinato-Pirola, et al.
Published: (2025-01-01) -
Prevalence of Dental Anomalies in Deciduous and Permanent Dentition of Cleft Lip and Palate Patients
by: Bernardo Olsson, et al.
Published: (2025-01-01) -
Appearance-related distress impacts psychological symptoms in Chinese patients with cleft lip
by: Yichun Yang, et al.
Published: (2025-01-01)