AIMC Topic: Radiography, Dental
Clear Filters Showing 31 to 40 of 59 articles
Fully automated film mounting in dental radiography: a deep learning model.
BMC medical imaging
Aug 18, 2023
BACKGROUND: Dental film mounting is an essential but time-consuming task in dental radiography, with manual methods often prone to errors. This study aims to develop a deep learning (DL) model for accurate automated classification and mounting of bot...
AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.
IEEE journal of biomedical and health informatics
Apr 14, 2022
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment...
RDFNet: A Fast Caries Detection Method Incorporating Transformer Mechanism.
Computational and mathematical methods in medicine
Nov 10, 2021
Dental caries is a prevalent disease of the human oral cavity. Given the lack of research on digital images for caries detection, we construct a caries detection dataset based on the caries images annotated by professional dentists and propose RDFNet...
Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review.
BioMed research international
Jun 22, 2021
OBJECTIVE: The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
A deep learning approach for dental implant planning in cone-beam computed tomography images.
BMC medical imaging
May 19, 2021
BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.
Intraoral radiograph anatomical region classification using neural networks.
International journal of computer assisted radiology and surgery
Feb 24, 2021
PURPOSE: Dental radiography represents 13% of all radiological diagnostic imaging. Eliminating the need for manual classification of digital intraoral radiographs could be especially impactful in terms of time savings and metadata quality. However, a...
Age-group determination of living individuals using first molar images based on artificial intelligence.
Scientific reports
Jan 13, 2021
Dental age estimation of living individuals is difficult and challenging, and there is no consensus method in adults with permanent dentition. Thus, we aimed to provide an accurate and robust artificial intelligence (AI)-based diagnostic system for a...
Transfer Learning Based Automatic Human Identification using Dental Traits- An Aid to Forensic Odontology.
Journal of forensic and legal medicine
Sep 29, 2020
Forensic Odontology deals with identifying humans based on their dental traits because of their robust nature. Classical methods of human identification require more manual effort and are difficult to use for large number of Images. A Novel way of au...
Image denoising by transfer learning of generative adversarial network for dental CT.
Biomedical physics & engineering express
Sep 8, 2020
The successful development of the image denoising techniques for low-dose computed tomography (LDCT) was largely owing to the public-domain availability of spatially-aligned high- and low-dose CT image pairs. Even though low-dose CT scans are also hi...
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.
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