In this paper, we develop methodology to locate cephalometric landmarks on X-ray images based on probabilistic relaxation, which combines local contextual information from the general shape of the bones of the head (used as measurements specific to each landmark in the form of its shape context) and relational information, expressing the relative position of the landmarks with respect to each other.
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Applications of artificial intelligence in orthodontics: a bibliometric and visual analysis.
Clin Oral Investig
January 2025
Department of General Surgery and Surgical-Medical Specialties, Section of Orthodontics, University of Catania, Via S. Sofia 68, Catania, 95124, Italy.
Objectives: To conduct a comprehensive bibliometric analysis of the literature on artificial intelligence (AI) applications in orthodontics to provide a detailed overview of the current research trends, influential works, and future directions.
Materials And Methods: A research strategy in The Web of Science Core Collection has been conducted to identify original articles regarding the use of AI in orthodontics. Articles were screened and selected by two independent reviewers and the following data were imported and processed for analysis: rankings, centrality metrics, publication trends, co-occurrence and clustering of keywords, journals, articles, authors, nations, and organizations.
Objectives: To compare differences in craniofacial growth prediction results for Korean and American children according to growth prediction models developed using Korean and American longitudinal growth data.
Materials And Methods: Growth prediction models based on cephalometric landmarks were built for each population using longitudinally taken lateral cephalograms of Korean children and American children of northern European origin. The sample sizes of the serial datasets were 679 and 1257 for Korean and American children, respectively.
The Accuracy of Algorithms Used by Artificial Intelligence in Cephalometric Points Detection: A Systematic Review.
Bioengineering (Basel)
December 2024
Departamento de Odontoestomatología, Facultad de Medicina y Ciencias de la Salud, Universidad de Barcelona, Campus Bellvitge, 08097 L'Hospitalet de Llobregat, Barcelona, Spain.
The use of artificial intelligence in orthodontics is emerging as a tool for localizing cephalometric points in two-dimensional X-rays. AI systems are being evaluated for their accuracy and efficiency compared to conventional methods performed by professionals. The main objective of this study is to identify the artificial intelligence algorithms that yield the best results for cephalometric landmark localization, along with their learning system.
View Article and Find Full Text PDFAccuracy of cephalometric landmark and cephalometric analysis from lateral facial photograph by using CNN-based algorithm.
Sci Rep
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Department of Orthodontics, Tokyo Dental College, 2-9-18, Kandamisaki-Cho, Chiyoda- Ku, Tokyo, 101-006, Japan.
Cephalometric analysis is the primary diagnosis method in orthodontics. In our previous study, the algorithm was developed to estimate cephalometric landmarks from lateral facial photographs of patients with normal occlusion. This study evaluates the estimation accuracy by the algorithm trained on a dataset of 2320 patients with added malocclusion patients and the analysis values.
View Article and Find Full Text PDFObjective: Aim: To investigate the usage trends of different 3D digital technologies in modern orthodontics during the previous eight years to identify their future prospects.
Patients And Methods: Materials and Methods: A systematic literature search on PubMed revealed 258,059 publications concerning digital technologies in modern orthodontics. Amongst 125 eligible articles, we chose 37 high quality articles.
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