AIMC Topic: Cephalometry

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Automated classification of skeletal malocclusion in German orthodontic patients.

Clinical oral investigations Aug 5, 2025
OBJECTIVES: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differen...
Machine Learning Prospective Studies Female Adult Humans Neural Networks, Computer Artificial Intelligence Child Cephalometry Germany Malocclusion Cross-Sectional Studies Male Deep Learning Adolescent
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Use of X means and C4.5 algorithms on lateral cephalometric measurements to identify craniofacial patterns.

BMC oral health Jul 26, 2025
BACKGROUND: Craniofacial phenotyping is essential for individualized orthodontic diagnosis and treatment planning. Traditional skeletal classifications, such as the ANB angle, may oversimplify complex relationships among malocclusion types. Machine l...
Male Adolescent Child Cluster Analysis Humans Machine Learning Algorithms Female Decision Trees Cephalometry Malocclusion
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Multimodal deep learning for cephalometric landmark detection and treatment prediction.

Scientific reports Jul 12, 2025
In orthodontics and maxillofacial surgery, accurate cephalometric analysis and treatment outcome prediction are critical for clinical decision-making. Traditional approaches rely on manual landmark identification, which is time-consuming and subject ...
Image Processing, Computer-Assisted Treatment Outcome Anatomic Landmarks Cephalometry Humans Deep Learning Cone-Beam Computed Tomography
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Automated landmark-based mid-sagittal plane: reliability for 3-dimensional mandibular asymmetry assessment on head CT scans.

Clinical oral investigations May 26, 2025
OBJECTIVE: The determination of the mid-sagittal plane (MSP) on three-dimensional (3D) head imaging is key to the assessment of facial asymmetry. The aim of this study was to evaluate the reliability of an automated landmark-based MSP to quantify man...
Male Adolescent Imaging, Three-Dimensional Mandible Anatomic Landmarks Cephalometry Facial Asymmetry Tomography, X-Ray Computed Female Reproducibility of Results Adult Humans
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Digital and artificial intelligence-assisted cephalometric training effectively enhanced students' landmarking accuracy in preclinical orthodontic education.

BMC oral health Apr 24, 2025
BACKGROUND: Digital cephalometric analyses, including those assisted by artificial intelligence (AI), are widely used in clinical practice. Similarly, computer-assisted learning has demonstrated teaching outcomes comparable to those of traditional me...
Artificial Intelligence Female Male Anatomic Landmarks Cephalometry Education, Dental Orthodontics Humans Computer-Assisted Instruction Students, Dental
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Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.

Scientific reports Apr 13, 2025
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...
Malocclusion, Angle Class III Adult Malocclusion, Angle Class I Cross-Sectional Studies Male Adolescent Child Principal Component Analysis Cephalometry Germany Machine Learning Prospective Studies Female Young Adult Humans
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Predicting changes of incisor and facial profile following orthodontic treatment: a machine learning approach.

Head & face medicine Mar 28, 2025
BACKGROUND: Facial aesthetics is one of major motivations for seeking orthodontic treatment. However, even for experienced professionals, the impact and extent of incisor and soft tissue changes remain largely empirical. With the application of inter...
Cephalometry Face Malocclusion Female Humans Orthodontics, Corrective Young Adult Neural Networks, Computer Incisor Male Machine Learning Esthetics, Dental Adolescent
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Deep learning based quantitative cervical vertebral maturation analysis.

Head & face medicine Mar 26, 2025
OBJECTIVES: This study aimed to enhance clinical diagnostics for quantitative cervical vertebral maturation (QCVM) staging with precise landmark localization. Existing methods are often subjective and time-consuming, while deep learning alternatives ...
Deep Learning Cephalometry Adolescent Humans Cervical Vertebrae Child Neural Networks, Computer Age Determination by Skeleton Anatomic Landmarks Female Male
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Classification of skeletal discrepancies by machine learning based on three-dimensional facial scans.

International journal of oral and maxillofacial surgery Mar 17, 2025
The aim of this study was to use machine learning (ML) to classify sagittal and vertical skeletal discrepancies in three-dimensional (3D) facial scans, as well as to evaluate shape variability. 3D facial scans from 435 pre-orthodontic patients were s...
Male Adolescent Imaging, Three-Dimensional Principal Component Analysis Humans Anatomic Landmarks Machine Learning Cephalometry Female Face Adult Malocclusion
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Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.

Nature communications Mar 16, 2025
Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purposes. Accurate prediction of surgical outcomes is essential for selecting the optimal treatment plan a...
Postoperative Period Orthognathic Surgical Procedures Graph Neural Networks Neural Networks, Computer Male Female Treatment Outcome Young Adult Cephalometry Adult Humans
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