AIMC Topic: Tooth

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Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

Journal of dentistry Mar 30, 2024
OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the car...
Humans Deep Learning Image Processing, Computer-Assisted Dental Caries Neural Networks, Computer Sensitivity and Specificity Dentists Radiography, Dental Radiography, Bitewing Tooth
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Artificial neural networks reconstruct missing perikymata in worn teeth.

Anatomical record (Hoboken, N.J. : 2007) Mar 11, 2024
Dental evolutionary studies in hominins are key to understanding how our ancestors and close fossil relatives grew from the early stages of embryogenesis into adults. In a sense, teeth are like an airplane's 'black box' as they record important varia...
Hominidae Biological Evolution Fossils Neural Networks, Computer Tooth Wear Animals Dental Enamel Humans Tooth
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DilatedToothSegNet: Tooth Segmentation Network on 3D Dental Meshes Through Increasing Receptive Vision.

Journal of imaging informatics in medicine Mar 5, 2024
The utilization of advanced intraoral scanners to acquire 3D dental models has gained significant popularity in the fields of dentistry and orthodontics. Accurate segmentation and labeling of teeth on digitized 3D dental surface models are crucial fo...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Tooth Models, Dental Algorithms Deep Learning Imaging, Three-Dimensional
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Tooth numbering and classification on bitewing radiographs: an artificial intelligence pilot study.

Oral surgery, oral medicine, oral pathology and oral radiology Feb 20, 2024
OBJECTIVE: The aim of this study is to assess the efficacy of employing a deep learning methodology for the automated identification and enumeration of permanent teeth in bitewing radiographs. The experimental procedures and techniques employed in th...
Humans Turkey Tooth Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Artificial Intelligence Radiography, Bitewing Deep Learning Algorithms Pilot Projects
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Performance evaluation of three versions of a convolutional neural network for object detection and segmentation using a multiclass and reduced panoramic radiograph dataset.

Journal of dentistry Feb 16, 2024
OBJECTIVES: To evaluate the diagnostic performance of three versions of a deep-learning convolutional neural network in terms of object detection and segmentation using a multiclass panoramic radiograph dataset.
Dental Implants Tooth Maxilla Image Processing, Computer-Assisted Radiography, Panoramic Mandibular Nerve Deep Learning Mandible Humans Neural Networks, Computer
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Deep learning-based tooth segmentation methods in medical imaging: A review.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Feb 5, 2024
Deep learning approaches for tooth segmentation employ convolutional neural networks (CNNs) or Transformers to derive tooth feature maps from extensive training datasets. Tooth segmentation serves as a critical prerequisite for clinical dental analys...
Image Processing, Computer-Assisted Tooth Cone-Beam Computed Tomography Imaging, Three-Dimensional Neural Networks, Computer Deep Learning
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Automatic dental age calculation from panoramic radiographs using deep learning: a two-stage approach with object detection and image classification.

BMC oral health Jan 31, 2024
BACKGROUND: Dental age is crucial for treatment planning in pediatric and orthodontic dentistry. Dental age calculation methods can be categorized into morphological, biochemical, and radiological methods. Radiological methods are commonly used becau...
Dental Pulp Radiography, Panoramic Tooth Age Determination by Teeth Humans Deep Learning Child
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Autologous Transplantation Tooth Guide Design Based on Deep Learning.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons Sep 20, 2023
BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone t...
Transplantation, Autologous Tooth Humans Deep Learning Cone-Beam Computed Tomography Retrospective Studies Image Processing, Computer-Assisted Cross-Sectional Studies
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Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study.

Journal of dentistry Jul 28, 2023
OBJECTIVES: To train and validate a cloud-based convolutional neural network (CNN) model for automated segmentation (AS) of dental implant and attached prosthetic crown on cone-beam computed tomography (CBCT) images.
Dental Implants Tooth Deep Learning Humans Cone-Beam Computed Tomography Neural Networks, Computer Image Processing, Computer-Assisted
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Effect of data size on tooth numbering performance via artificial intelligence using panoramic radiographs.

Oral radiology Jul 5, 2023
OBJECTIVE: This study aims to investigate the effect of number of data on model performance, for the detection of tooth numbering problem on dental panoramic radiographs, with the help of image processing and deep learning algorithms.
Radiography, Panoramic Tooth Adult Image Processing, Computer-Assisted Artificial Intelligence Humans Algorithms
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