AIMC Topic: Cephalometry

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[Comparative study of two software for the detection of cephalometric landmarks by artificial intelligence].

L' Orthodontie francaise Mar 1, 2022
INTRODUCTION: Manual, tedious cephalometric analyzes of a lack of productivity (errors in plotting and measurement) making the prospect of a fully automated algorithm turning out attractive. The objectives of the study were to evaluate the positionin...
Humans Artificial Intelligence Software Cephalometry
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Surgery-First Orthognathic Approach to Correct Facial Asymmetry: Artificial Intelligence-Based Cephalometric Analysis.

Plastic and reconstructive surgery Mar 1, 2022
BACKGROUND: The surgery-first orthognathic approach has been applied at our institution since 2007. However, its indications remain debated. The aim of this study was to investigate the reliability of the surgery-first approach to correct facial asym...
Humans Artificial Intelligence Orthodontics, Corrective Orthognathic Surgery Retrospective Studies Cephalometry Treatment Outcome Facial Asymmetry
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Fully automated identification of cephalometric landmarks for upper airway assessment using cascaded convolutional neural networks.

European journal of orthodontics Jan 25, 2022
OBJECTIVES: The aim of the study was to evaluate the accuracy of a cascaded two-stage convolutional neural network (CNN) model in detecting upper airway (UA) soft tissue landmarks in comparison with the skeletal landmarks on the lateral cephalometric...
Face Palate, Soft Neural Networks, Computer Algorithms Adult Cephalometry Humans
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Bone age assessment from lateral cephalograms using deep learning algorithms in the Indian population.

Indian journal of dental research : official publication of Indian Society for Dental Research Jan 1, 2022
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...
Young Adult Adult Machine Learning Algorithms Child Humans Cephalometry Neural Networks, Computer Deep Learning Adolescent
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Anatomical Landmark Detection using Deep Appearance-Context Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Accurate identification of anatomical landmarks is a crucial step in medical image analysis. While deep neural networks have shown impressive performance on computer vision tasks, they rely on a large amount of data, which is often not available. In ...
Spine Radiography Cephalometry Neural Networks, Computer
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Evaluation of automated cephalometric analysis based on the latest deep learning method.

The Angle orthodontist May 1, 2021
OBJECTIVES: To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according to the test style of the worldwide AI challenges at t...
Cephalometry Deep Learning Humans Radiography Algorithms
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Evaluation of the efficiency of computerized algorithms to formulate a decision support system for deepbite treatment planning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Apr 1, 2021
INTRODUCTION: This study aimed to evaluate the efficiency of a newly constructed computer-based decision support system (DSS) on the basis of artificial intelligence technology and designed to plan treatment for patients with a deep overbite.
Artificial Intelligence Algorithms Mandible Cephalometry Humans Malocclusion Dentition, Permanent
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[Cephalometric analysis of lateral skull X-ray images using soft computing components in the search for key points].

Stomatologiia Jan 1, 2021
THE AIM OF THE STUDY: Was to investigate the efficiency of decoding teleradiological studies using an algorithm based on the use of convolutional neural networks - a simple convolutional architecture, as well as an extended U-Net architecture.
X-Rays Cephalometry Skull Image Processing, Computer-Assisted Humans Radiography Neural Networks, Computer
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How much deep learning is enough for automatic identification to be reliable?

The Angle orthodontist Nov 1, 2020
OBJECTIVES: To determine the optimal quantity of learning data needed to develop artificial intelligence (AI) that can automatically identify cephalometric landmarks.
Radiography Cephalometry Artificial Intelligence Deep Learning Humans
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[Cranial Facial 3D Biometry: Statistical analysis of Class II disharmonies].

L' Orthodontie francaise Jun 1, 2020
We could study Cone Beam documents of patients consulting in ORL with standard Angle Class I occlusion (45 ND), patients consulting in orthodontics with an orthodontic Class II (51 APNS) and patients with a surgical Class II (83 APS). The used 3D bio...
Biometry Artificial Intelligence Skull Cephalometry Malocclusion, Angle Class II Humans
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