AIMC Topic: Radiography, Dental
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Convolutional neural networks for dental image diagnostics: A scoping review.
Journal of dentistry
Nov 5, 2019
OBJECTIVES: Convolutional neural networks (CNNs) are increasingly applied for medical image diagnostics. We performed a scoping review, exploring (1) use cases, (2) methodologies and (3) findings of studies applying CNN on dental image material.
The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review.
Dento maxillo facial radiology
Aug 14, 2019
OBJECTIVES: To investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR).
A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films.
Scientific reports
Mar 7, 2019
We propose using faster regions with convolutional neural network features (faster R-CNN) in the TensorFlow tool package to detect and number teeth in dental periapical films. To improve detection precisions, we propose three post-processing techniqu...
Artifact correction in low-dose dental CT imaging using Wasserstein generative adversarial networks.
Medical physics
Feb 14, 2019
PURPOSE: In recent years, health risks concerning high-dose x-ray radiation have become a major concern in dental computed tomography (CT) examinations. Therefore, adopting low-dose computed tomography (LDCT) technology has become a major focus in th...
An effective teeth recognition method using label tree with cascade network structure.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 17, 2018
In this article, we apply the deep learning technique to medical field for the teeth detection and classification of dental periapical radiographs, which is important for the medical curing and postmortem identification. We detect teeth in an input X...
3D Tooth Segmentation and Labeling Using Deep Convolutional Neural Networks.
IEEE transactions on visualization and computer graphics
May 22, 2018
In this paper, we present a novel approach for 3D dental model segmentation via deep Convolutional Neural Networks (CNNs). Traditional geometry-based methods tend to receive undesirable results due to the complex appearance of human teeth (e.g., miss...
Classification of teeth in cone-beam CT using deep convolutional neural network.
Computers in biology and medicine
Nov 12, 2016
Dental records play an important role in forensic identification. To this end, postmortem dental findings and teeth conditions are recorded in a dental chart and compared with those of antemortem records. However, most dentists are inexperienced at r...
The detection of apical radiolucencies in periapical radiographs: A comparison between an artificial intelligence platform and expert endodontists with CBCT serving as the diagnostic benchmark.
International endodontic journal
Aug 1, 2025
AIM: Accurate detection of periapical radiolucent lesions (PARLs) is crucial for endodontic diagnosis. While cone beam computed tomography (CBCT) is considered the radiographic gold standard for detecting PARLs in non-root filled teeth, its use is of...
Evaluating artificial intelligence chatbots for patient education in oral and maxillofacial radiology.
Oral surgery, oral medicine, oral pathology and oral radiology
Jun 1, 2025
OBJECTIVE: This study aimed to compare the quality and readability of the responses generated by 3 publicly available artificial intelligence (AI) chatbots in answering frequently asked questions (FAQs) related to Oral and Maxillofacial Radiology (OM...
A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs.
BMC oral health
May 26, 2025
PURPOSE: Numerous studies have investigated the use of convolutional neural network (CNN) models for detecting periapical lesions(PLs). However, limited research has focused on evaluating their potential in assisting clinicians with diagnosis. This s...
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