ArticleScientific reports2021
Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 37 citations in OpenAlex.
- Three-dimensional facial gestalt analysis for three neurodevelopmental disorders: Koolen-de Vries, Jansen-de Vries and KBG syndrome.European journal of human genetics : EJHG · 2026Article
- BabyFlow: 3D modeling of realistic and expressive infant faces.Scientific reports · 2026Article
- Quantification and visualization of 3D facial aging in individuals of European ancestry.GeroScience · 2026Article
- Clusters in craniofacial microsomia and microtia according to facial morphology and craniofacial anomalies.European journal of pediatrics · 2026Article
- How Sex Shapes Facial Morphology in Adults: A 3D Geometric Morphometric Study.Diagnostics (Basel, Switzerland) · 2026Article
- Advancing genotype-phenotype analysis through 3D facial morphometry: insights from Cri-du-Chat syndrome.Journal of medical genetics · 2026Article
- 3D anthropometry of the nasolabial region in children aged 3 to 9 months as reference database for clinical assessment.Scientific reports · 2025Article
- Exploring the association between SNPs and facial morphology in a Spanish population.Scientific reports · 2025Article
- Three-Dimensional Geometric Morphometric Characterization of Facial Sexual Dimorphism in Juveniles.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- Fetal face shape analysis from prenatal 3D ultrasound images.Scientific reports · 2024Article
- An interactive atlas of three-dimensional syndromic facial morphology.American journal of human genetics · 2024Article
- Article
- Longitudinal Three-Dimensional Stereophotogrammetric Growth Analysis in Infants with Unilateral Cleft Lip and Palate from 3 to 12 Months of Age.Journal of clinical medicine · 2023Article
- Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology.Journal of anatomy · 2023Article
- Influence of age and diet consistency on the oral muscle pressure of orthodontically treated and untreated subjects with normal occlusion and comparison of their 3D facial shape.Clinical oral investigations · 2023Article
- Frem1 activity is regulated by Sonic hedgehog signaling in the cranial neural crest mesenchyme during midfacial morphogenesis.Developmental dynamics : an official publication of the American Association of Anatomists · 2023Article
- Detecting 3D syndromic faces as outliers using unsupervised normalizing flow models.Artificial intelligence in medicine · 2022Article
- Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology.Annual review of genomics and human genetics · 2022Review
- Refining nosology by modelling variation among facial phenotypes: the RASopathies.Journal of medical genetics · 2022Article
Corrections and comments
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Authors and funding
15 authors at 12 institutions in 6 countries.
Funding
Abstract
Craniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype-phenotype relations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.