AIMC Topic: Cephalometry
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Deep convolutional neural network-the evaluation of cervical vertebrae maturation.
Oral radiology
Mar 9, 2023
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...
Evaluation of the accuracy of fully automatic cephalometric analysis software with artificial intelligence algorithm.
Orthodontics & craniofacial research
Jan 24, 2023
OBJECTIVE: The aim of this study is to evaluate whether fully automatic cephalometric analysis software with artificial intelligence algorithms is as accurate as non-automated cephalometric analysis software for clinical diagnosis and research.
Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis.
Journal of digital imaging
Jan 5, 2023
Using computer vision through artificial intelligence (AI) is one of the main technological advances in dentistry. However, the existing literature on the practical application of AI for detecting cephalometric landmarks of orthodontic interest in di...
Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis.
Scientific reports
Nov 29, 2022
Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radiographs display a three-dimensional structure on a two-dimensional plane, inaccuracies may be produce...
Automated calibration system for length measurement of lateral cephalometry based on deep learning.
Physics in medicine and biology
Nov 18, 2022
. Cephalometric analysis has been significantly facilitated by artificial intelligence (AI) in recent years. For digital cephalograms, linear measurements are conducted based on the length calibration process, which has not been automatized in curren...
Artificial intelligence system for automated landmark localization and analysis of cephalometry.
Dento maxillo facial radiology
Nov 16, 2022
OBJECTIVES: Cephalometric analysis is essential for diagnosis, treatment planning and outcome assessment of orthodontics and orthognathic surgery. Utilizing artificial intelligence (AI) to achieve automated landmark localization has proved feasible a...
DEEP LEARNING ALGORITHMS HAVE HIGH ACCURACY FOR AUTOMATED LANDMARK DETECTION ON 2D LATERAL CEPHALOGRAMS.
The journal of evidence-based dental practice
Oct 22, 2022
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Deep learning for cephalometric landmark detection: systematic review and meta-analysis. Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, Demarco F, Krois J. Clin Oral Invest...
Comparison of AudaxCeph®'s fully automated cephalometric tracing technology to a semi-automated approach by human examiners.
International orthodontics
Sep 14, 2022
OBJECTIVE: To compare the reliability of cephalometric landmark identification by an automated tracing software based on convolutional neural networks to human tracers.
Automated analysis of three-dimensional CBCT images taken in natural head position that combines facial profile processing and multiple deep-learning models.
Computer methods and programs in biomedicine
Sep 9, 2022
BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis and treatment planning of orthodontic patients. Artificial intelligence, especially deep-learning t...
Automatic 3-Dimensional Cephalometric Landmarking via Deep Learning.
Journal of dental research
Aug 18, 2022
The increasing use of 3-dimensional (3D) imaging by orthodontists and maxillofacial surgeons to assess complex dentofacial deformities and plan orthognathic surgeries implies a critical need for 3D cephalometric analysis. Although promising methods w...
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