Indian journal of dental research : official publication of Indian Society for Dental Research
37006005
PURPOSE: The assessment of bone age has applications in a wide variety of fields: from orthodontics to immigration. The traditional non-automated methods are time-consuming and subject to inter- and intra-observer variability. This is the first study...
INTRODUCTION: It has been suggested that human errors during manual tracing of linear/angular cephalometric parameters can be eliminated by using computer-aided analysis. The landmarks, however, are located manually and the computer system completes ...
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
36959014
INTRODUCTION: Prediction of lip prominence based on hard-tissue measurements could be helpful in orthodontic treatment planning and has been challenging and formidable thus far.
Deep learning algorithms based on automatic 3-dimensional (D) cephalometric marking points about people without craniomaxillofacial deformities has achieved good results. However, there has been no previous report about cleft lip and palate. The purp...
OBJECTIVES: This study aimed to automatically determine the cervical vertebral maturation (CVM) processes on lateral cephalometric radiograph images using a proposed deep learning-based convolutional neural network (CNN) model and to test the success...
OBJECTIVES: The aim of the present systematic review and meta-analysis is to assess the accuracy of automated landmarking using deep learning in comparison with manual tracing for cephalometric analysis of 3D medical images.
OBJECTIVE: Quantitative measurements of trigonocephaly can be used to characterize and track this phenotype, which is associated with metopic craniosynostosis. Traditionally, trigonocephaly metrics were extracted from CT scans; however, this method e...
OBJECTIVES: Due to advancing digitalisation, it is of interest to develop standardised and reproducible fully automated analysis methods of cranial structures in order to reduce the workload in diagnosis and treatment planning and to generate objecti...
BACKGROUND: The purpose of this study was to evaluate the accuracy of automatic cephalometric landmark localization and measurements using cephalometric analysis via artificial intelligence (AI) compared with computer-assisted manual analysis.
Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
37271999
To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. A total of 2 894 lateral cephalograms were collected in Department of Orthodo...