AIMC Topic: Cone-Beam Computed Tomography
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Automated diagnosis and classification of temporomandibular joint degenerative disease via artificial intelligence using CBCT imaging.
Journal of dentistry
Jan 25, 2025
OBJECTIVES: In this study, artificial intelligence (AI) techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.
A platform combining automatic segmentation and automatic measurement of the maxillary sinus and adjacent structures.
Clinical oral investigations
Jan 25, 2025
OBJECTIVES: To develop a platform including a deep convolutional neural network (DCNN) for automatic segmentation of the maxillary sinus (MS) and adjacent structures, and automatic algorithms for measuring 3-dimensional (3D) clinical parameters.
Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors.
Radiation oncology (London, England)
Jan 22, 2025
PURPOSE: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and mon...
A multi-modal dental dataset for semi-supervised deep learning image segmentation.
Scientific data
Jan 20, 2025
In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing...
Assessment of hard tissue changes after horizontal guided bone regeneration with the aid of deep learning CBCT segmentation.
Clinical oral investigations
Jan 13, 2025
OBJECTIVES: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.
Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models.
BMC oral health
Jan 8, 2025
BACKGROUND: A comprehensive analysis of the occlusal plane (OP) inclination in predicting anteroposterior mandibular position (APMP) changes is still lacking. This study aimed to analyse the relationships between inclinations of different OPs and APM...
Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients.
Orthodontics & craniofacial research
Jan 4, 2025
OBJECTIVE: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analysed with ...
Automated Cone Beam Computed Tomography Segmentation of Multiple Impacted Teeth With or Without Association to Rare Diseases: Evaluation of Four Deep Learning-Based Methods.
Orthodontics & craniofacial research
Jan 2, 2025
OBJECTIVE: To assess the accuracy of three commercially available and one open-source deep learning (DL) solutions for automatic tooth segmentation in cone beam computed tomography (CBCT) images of patients with multiple dental impactions.
Efficacy of a deep learning system for automatic analysis of the comprehensive spatial relationship between the mandibular third molar and inferior alveolar canal on panoramic radiographs.
Oral surgery, oral medicine, oral pathology and oral radiology
Jan 2, 2025
OBJECTIVE: To develop and evaluate a deep learning (DL) system for predicting the contact and relative position relationships between the mandibular third molar (M3) and inferior alveolar canal (IAC) using panoramic radiographs (PRs) for preoperative...
Validation of a novel tool for automated tooth modelling by fusion of CBCT-derived roots with the respective IOS-derived crowns.
Journal of dentistry
Dec 30, 2024
OBJECTIVES: To validate a novel artificial intelligence (AI)-based tool for automated tooth modelling by fusing cone beam computed tomography (CBCT)-derived roots with corresponding intraoral scanner (IOS)-derived crowns.
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