AIMC Topic: Cephalometry

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Deep learning approaches for quantitative and qualitative assessment of cervical vertebral maturation staging systems.

PloS one
To investigate the potential of artificial intelligence (AI) in Cervical Vertebral Maturation (CVM) staging, we developed and compared AI-based qualitative CVM and AI-based quantitative QCVM methods. A dataset of 3,600 lateral cephalometric images fr...

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods.

The Angle orthodontist
OBJECTIVES: To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models.

Can artificial intelligence-driven cephalometric analysis replace manual tracing? A systematic review and meta-analysis.

European journal of orthodontics
OBJECTIVES: This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and thre...

Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.

Dento maxillo facial radiology
OBJECTIVES: To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations.

[Automated cephalometric landmark identification and location based on convolutional neural network].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
To develop an automated landmark location system applicable to the case of landmark missing. Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to Ja...

Using a New Deep Learning Method for 3D Cephalometry in Patients With Hemifacial Microsomia.

Annals of plastic surgery
Deep learning algorithms based on automatic 3D cephalometric marking points about people without craniomaxillofacial deformities have achieved good results. However, there has been no previous report about hemifacial microsomia (HFM). The purpose of ...

An automatic cephalometric landmark detection method based on heatmap regression and Monte Carlo dropout.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cephalometric analysis plays an important role in orthodontic diagnosis and treatment planning. It depends on the detection of multiple landmarks, while the process is time-consuming and tedious. Although some deep learning-based automatic landmark d...

[Automated diagnostic classification with lateral cephalograms based on deep learning network model].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
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...