AIMC Topic: Mandible
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Automatic deep learning segmentation of mandibular periodontal bone topography on cone-beam computed tomography images.
Journal of dentistry
Aug 1, 2025
OBJECTIVES: This study evaluated the performance of a multi-stage Segmentation Residual Network (SegResNet)-based deep learning (DL) model for the automatic segmentation of cone-beam computed tomography (CBCT) images of patients with stage III and IV...
ChatIOS: Improving automatic 3-dimensional tooth segmentation via GPT-4V and multimodal pre-training.
Journal of dentistry
Jun 1, 2025
OBJECTIVES: This study aims to propose a framework that integrates GPT-4V, a recent advanced version of ChatGPT, and multimodal pre-training techniques to enhance deep learning algorithms for 3-dimensional (3D) tooth segmentation in scans produced by...
Automated diagnosis for extraction difficulty of maxillary and mandibular third molars and post-extraction complications using deep learning.
Scientific reports
May 30, 2025
Optimal surgical methods require accurate prediction of extraction difficulty and complications. Although various automated methods related to third molar (M3) extraction have been proposed, none fully predict both extraction difficulty and post-extr...
A Compact Surgical Robot System for Craniomaxillofacial Surgery and its Preliminary Study.
The Journal of craniofacial surgery
May 13, 2025
Craniomaxillofacial surgery has the characteristics of complex anatomical structure, narrow surgical field, and easy damage to nerves, blood vessels, and other structures. Compared with the traditional bare-hand operation, robot-assisted craniofacial...
Deep learning-based segmentation of the mandibular canals in cone-beam CT reaches human-level performance.
Dento maxillo facial radiology
May 1, 2025
OBJECTIVES: This study evaluated the accuracy and reliability of deep learning-based segmentation techniques for mandibular canal identification in cone-beam CT (CBCT) data to provide a reliable and efficient support tool for dental implant treatment...
[Personalized mandibular reconstruction assisted by three-dimensional retrieval model based on fully connected neural network and a database of mandibles].
Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
Apr 18, 2025
OBJECTIVE: To propose a new protocol for personalized mandibular reconstruction assisted by three-dimensional (3D) retrieval model based on fully connected neural network (FCNN) and a database of mandibles, and to verify clinical feasibility of the p...
Assessment of deep learning technique for fully automated mandibular segmentation.
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
Feb 1, 2025
INTRODUCTION: This study aimed to assess the precision of an open-source, clinician-trained, and user-friendly convolutional neural network-based model for automatically segmenting the mandible.
Development and evaluation of a deep learning model to reduce exomass-related metal artefacts in cone-beam CT: an ex vivo study using porcine mandibles.
Dento maxillo facial radiology
Feb 1, 2025
OBJECTIVES: To develop and evaluate a deep learning (DL) model to reduce metal artefacts originating from the exomass in cone-beam CT (CBCT) of the jaws.
Temporomandibular joint and masticatory muscles morphometry and morphology in healthy subjects and individuals with temporomandibular dysfunction: An anatomical, radiological, and machine learning application study.
Medicine
Dec 13, 2024
The study aimed to compare the morphometric and morphologic analyses of the bone structures of temporomandibular joint and masticatory muscles on Cone beam computed tomography (CBCT) in 62 healthy subjects and 33 subjects with temporomandibular dysfu...
[A pilot study on clinical application of three-dimensional morphological completion of lesioned mandibles assisted by generative adversarial networks].
Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
Dec 9, 2024
To explore the clinical application pathway of the CT generative adversarial networks (CTGANs) algorithm in mandibular reconstruction surgery, aiming to provide a valuable reference for this procedure. A clinical exploratory study was conducted, 27...
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