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Artificial intelligence (AI) diagnostic tools: utilizing a convolutional neural network (CNN) to assess periodontal bone level radiographically—a retrospective study
BackgroundThe purpose of this investigation was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN)...
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Deep convolutional neural network—the evaluation of cervical vertebrae maturation
ObjectivesThis study aimed to automatically determine the cervical vertebral maturation (CVM) processes on lateral cephalometric radiograph images...
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Influence of growth structures and fixed appliances on automated cephalometric landmark recognition with a customized convolutional neural network
BackgroundOne of the main uses of artificial intelligence in the field of orthodontics is automated cephalometric analysis. Aim of the present study...
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Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis
ObjectivesWe aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to...
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Tooth caries classification with quantitative light-induced fluorescence (QLF) images using convolutional neural network for permanent teeth in vivo
BackgroundOwing to the remarkable advancements of artificial intelligence (AI) applications, AI-based detection of dental caries is continuously...
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Dental Caries diagnosis from bitewing images using convolutional neural networks
BackgroundDental caries , also known as tooth decay , is a widespread and long-standing condition that affects people of all ages. This ailment is...
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Dental bitewing radiographs segmentation using deep learning-based convolutional neural network algorithms
ObjectivesDental radiographs, particularly bitewing radiographs, are widely used in dental diagnosis and treatment Dental image segmentation is...
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A population-based study to assess two convolutional neural networks for dental age estimation
BackgroundDental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed...
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Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning-based convolutional neural network algorithm
ObjectivesArtificial intelligence (AI) techniques like convolutional neural network (CNN) are a promising breakthrough that can help clinicians...
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Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images
ObjectiveTo qualitatively and quantitatively assess integrated segmentation of three convolutional neural network (CNN) models for the creation of a...
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Detection and classification of mandibular fracture on CT scan using deep convolutional neural network
ObjectivesThis study aimed to evaluate the accuracy and reliability of convolutional neural networks (CNNs) for the detection and classification of...
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Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs
ObjectivesThis study aimed to investigate the effectiveness of deep convolutional neural network (CNN) in the diagnosis of interproximal caries...
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Automatic detection and segmentation of morphological changes of the maxillary sinus mucosa on cone-beam computed tomography images using a three-dimensional convolutional neural network
ObjectivesTo propose and evaluate a convolutional neural network (CNN) algorithm for automatic detection and segmentation of mucosal thickening (MT)...
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Automated methods for sella turcica segmentation on cephalometric radiographic data using deep learning (CNN) techniques
ObjectiveThe objective of this work is to present a novel technique using convolutional neural network (CNN) architectures for automatic segmentation...
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Deep semi-supervised learning for automatic segmentation of inferior alveolar nerve using a convolutional neural network
BackgroundThe inferior alveolar nerve (IAN) innervates and regulates the sensation of the mandibular teeth and lower lip. The position of the IAN...
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Enhancing oral squamous cell carcinoma detection: a novel approach using improved EfficientNet architecture
ProblemOral squamous cell carcinoma (OSCC) is the eighth most prevalent cancer globally, leading to the loss of structural integrity within the oral...
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ResMIBCU-Net: an encoder–decoder network with residual blocks, modified inverted residual block, and bi-directional ConvLSTM for impacted tooth segmentation in panoramic X-ray images
ObjectiveImpacted tooth is a common problem that can occur at any age, causing tooth decay, root resorption, and pain in the later stages. In recent...
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Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review
BackgroundThe aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the...
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A novel deep learning-based perspective for tooth numbering and caries detection
ObjectivesThe aim of this study was automatically detecting and numbering teeth in digital bitewing radiographs obtained from patients, and...
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Improving accuracy of early dental carious lesions detection using deep learning-based automated method
ObjectiveTo investigate the effectiveness of a convolutional neural network (CNN) in detecting healthy teeth and early carious lesions on occlusal...
