Open-Source 3D Morphing Software for Facial Plastic Surgery and Facial Landmark Detection Research and Open Access Face Data Set Based on Deep Learning (Artificial Intelligence) Generated Synthetic 3D Models.

Background: The scarcity of 3D facial models presents a significant hurdle for researchers and educators. Gathering such data demands substantial resources. Objective: To introduce an open-source 3D morphing software to generate 3D facial data sets for research and to provide a large sample data set that is based on synthetically generated 3D models. Methods: Software is developed to morph 3D facial models in bulk by altering landmark locations. Twenty synthetic 3D facial models are generated utilizing deep learning tools and 28 landmarks located on each. The measurements of synthetic models are confirmed to be realistic by comparing them with facial statistics. Several facial deformities and types are simulated at various magnitudes on 3D models to generate a large data set. Results: An open-source software and an open-access data set of 980 3D facial models, each with 28 landmark locations, are provided. Since the data set is based on synthetically generated 3D models, no institutional review board approval is required. Conclusion: The 3D morphing software and the large 3D data set are expected to benefit researchers and educators in the field of facial surgery and facial landmark detection.

Facial Surface Anthropometric Features and Measurements With an Emphasis on Rhinoplasty.

BACKGROUND: Facial features and measurements are utilized to analyze patients' faces for various reasons, including surgical planning, scientific communications, patient-surgeon communications, and post-surgery evaluations. OBJECTIVES: There are numerous descriptions regarding these features and measurements scattered throughout the literature, and the authors did not encounter a current compilation of these parameters in the medical literature. METHODS: A narrative literature review of the published medical literature for facial measurements used for facial analysis in rhinoplasty was conducted through the electronic databases MEDLINE/PubMed and Google Scholar, along with a citation search. RESULTS: A total of 61 facial features were identified: 45 points (25 bilateral, 20 unilateral), 5 lines (3 bilateral, 2 unilateral), 8 planes, and 3 areas.A total of 122 measurements were identified: 48 distances (6 bilateral, 42 unilateral), 57 angles (13 bilateral, 44 unilateral), and 17 ratios. Supplemental figures were created to depict all features and measurements utilizing a frontal, lateral, or basal view of the face. CONCLUSIONS: This paper provides the most comprehensive and current compilation of facial measurements to date. The authors believe this compilation will guide further developments (methodologies and software tools) for analyzing nasal structures and assessing the objective outcomes of facial surgeries, in particular rhinoplasty. Moreover, it will improve communication as a reference for facial measurements of facial surface anthropometry, in particular rhinoplasty.