AIMC Topic: Cephalometry

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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...
Tomography, X-Ray Computed Female Reproducibility of Results Adult Humans Mandible Anatomic Landmarks Cephalometry Facial Asymmetry Male Adolescent Imaging, Three-Dimensional
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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...
Orthodontics Computer-Assisted Instruction Students, Dental Humans Artificial Intelligence Female Cephalometry Education, Dental Male Anatomic Landmarks
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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 ...
Humans Machine Learning Prospective Studies Female Male Adolescent Child Principal Component Analysis Young Adult Adult Cross-Sectional Studies Malocclusion, Angle Class I Cephalometry Germany Malocclusion, Angle Class III
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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 Esthetics, Dental Orthodontics, Corrective Incisor Female Young Adult Humans Male Neural Networks, Computer Adolescent Machine Learning
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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 ...
Humans Cephalometry Cervical Vertebrae Age Determination by Skeleton Deep Learning Neural Networks, Computer Adolescent Child Female Anatomic Landmarks Male
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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...
Cephalometry Postoperative Period Orthognathic Surgical Procedures Graph Neural Networks Adult Male Treatment Outcome Female Young Adult Humans Neural Networks, Computer
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CephTransX: An attention enhanced feature fusion network leveraging neighborhood rough set approach for cephalometric landmark prediction.

Computers in biology and medicine Feb 25, 2025
The convergence of medical imaging, computer vision, and orthodontics has made automatic cephalometric landmark detection a pivotal area of research. Accurate cephalometric analysis is crucial in orthodontics, orthognathic and maxillofacial surgery f...
Image Processing, Computer-Assisted Humans Anatomic Landmarks Neural Networks, Computer Cephalometry Algorithms
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Accuracy of cephalometric landmark identification by artificial intelligence platform versus expert orthodontist in unilateral cleft palate patients: A retrospective study.

International orthodontics Feb 19, 2025
OBJECTIVE: The primary aim of the study was to evaluate the accuracy of automated artificial intelligence (AI) cephalometric landmark identification in cleft patients and compare it to landmarks identified by an expert orthodontist. The secondary obj...
Retrospective Studies Cleft Palate Female Humans Orthodontists Male Anatomic Landmarks Artificial Intelligence Adolescent Cephalometry Software Child
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Three-dimensional analysis of mandibular and condylar growth using artificial intelligence tools: a comparison of twin-block and Frankel II Appliances.

BMC oral health Feb 18, 2025
BACKGROUND: Analyzing the morphological growth changes upon mandibular advancement between Twin Block (TB) and Functional Regulator II (FR2) in Class II patients involves measuring the condylar and mandibular changes in terms of linear and volumetric...
Malocclusion, Angle Class II Mandible Humans Mandibular Condyle Cone-Beam Computed Tomography Cephalometry Orthodontic Appliances, Functional Male Artificial Intelligence Imaging, Three-Dimensional Mandibular Advancement Child Female
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Development of a diagnostic classification model for lateral cephalograms based on multitask learning.

BMC oral health Feb 15, 2025
OBJECTIVES: This study aimed to develop a cephalometric classification method based on multitask learning for eight diagnostic classifications.
Humans Female Sensitivity and Specificity Male Neural Networks, Computer Cephalometry Machine Learning Retrospective Studies
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