AIMC Topic: Tooth
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Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.
BMC oral health
Jun 6, 2025
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...
3D tooth identification for forensic dentistry using deep learning.
BMC oral health
Apr 30, 2025
The classification of intraoral teeth structures is a critical component in modern dental analysis and forensic dentistry. Traditional methods, relying on 2D imaging, often suffer from limitations in accuracy and comprehensiveness due to the complex ...
A Novel Hierarchical Cross-Stream Aggregation Neural Network for Semantic Segmentation of 3-D Dental Surface Models.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
Accurate teeth delineation on 3-D dental models is essential for individualized orthodontic treatment planning. Pioneering works like PointNet suggest a promising direction to conduct efficient and accurate 3-D dental model analyses in end-to-end lea...
A novel deep learning-based model for automated tooth detection and numbering in mixed and permanent dentition in occlusal photographs.
BMC oral health
Mar 29, 2025
BACKGROUND: While artificial intelligence-driven approaches have shown great promise in dental diagnosis and treatment planning, most research focuses on dental radiographs. Only three studies have explored automated tooth numbering in oral photograp...
Enhancing the classification of isolated theropod teeth using machine learning: a comparative study.
PeerJ
Mar 26, 2025
Classifying objects, such as taxonomic identification of fossils based on morphometric variables, is a time-consuming process. This task is further complicated by intra-class variability, which makes it ideal for automation via machine learning (ML) ...
Assessment of CNNs, transformers, and hybrid architectures in dental image segmentation.
Journal of dentistry
Mar 8, 2025
OBJECTIVES: Convolutional Neural Networks (CNNs) have long dominated image analysis in dentistry, reaching remarkable results in a range of different tasks. However, Transformer-based architectures, originally proposed for Natural Language Processing...
Accuracy of artificial intelligence-based segmentation in maxillofacial structures: a systematic review.
BMC oral health
Mar 7, 2025
OBJECTIVE: The aim of this review was to evaluate the accuracy of artificial intelligence (AI) in the segmentation of teeth, jawbone (maxilla, mandible with temporomandibular joint), and mandibular (inferior alveolar) canal in CBCT and CT scans.
Comparison of different dental age estimation methods with deep learning: Willems, Cameriere-European, London Atlas.
International journal of legal medicine
Feb 19, 2025
This study aimed to compare dental age estimates using Willems, Cameriere-Europe, London Atlas, and deep learning methods on panoramic radiographs of Turkish children. The dental ages of 1169 children (613 girls, 556 boys) who agreed to participate i...
Artificial intelligence system for automatic tooth detection and numbering in the mixed dentition in CBCT.
European journal of paediatric dentistry
Feb 1, 2025
AIM: To evaluate the effectiveness and accuracy of artificial intelligence (AI) by automating tooth segmentation in CBCT volumes of paediatric patients with mixed dentition, using nnU-Netv2 algorithm.
ML-based tooth shade assessment to prevent metamerism in different clinic lights.
Lasers in medical science
Jan 24, 2025
The aesthetic understanding has found its place in dental clinics and prosthetic dental treatment. Determining the appropriate prosthetic tooth color between the clinician, patient and technician is a difficult process due to metamerism. Metamerism, ...
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