AIMC Topic: Radiography, Panoramic

Clear Filters Showing 51 to 60 of 215 articles

DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.

Journal of forensic sciences
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...

Evaluation of tooth development stages with deep learning-based artificial intelligence algorithm.

BMC oral health
BACKGROUND: This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs from child patients.

Two-step deep learning models for detection and identification of the manufacturers and types of dental implants on panoramic radiographs.

Odontology
The purpose of this study is to develop two-step deep learning models that can automatically detect implant regions on panoramic radiographs and identify several types of implants. A total of 1,574 panoramic radiographs containing 3675 implants were ...

Estimation of human age using machine learning on panoramic radiographs for Brazilian patients.

Scientific reports
This paper addresses a relevant problem in Forensic Sciences by integrating radiological techniques with advanced machine learning methodologies to create a non-invasive, efficient, and less examiner-dependent approach to age estimation. Our study in...

Deep learning-based prediction of indication for cracked tooth extraction using panoramic radiography.

BMC oral health
BACKGROUND: We aimed to determine the feasibility of utilizing deep learning-based predictions of the indications for cracked tooth extraction using panoramic radiography.

RadImageNet and ImageNet as Datasets for Transfer Learning in the Assessment of Dental Radiographs: A Comparative Study.

Journal of imaging informatics in medicine
Transfer learning (TL) is an alternative approach to the full training of deep learning (DL) models from scratch and can transfer knowledge gained from large-scale data to solve different problems. ImageNet, which is a publicly available large-scale ...

Deep Learning for Predicting the Difficulty Level of Removing the Impacted Mandibular Third Molar.

International dental journal
BACKGROUND: Preoperative assessment of the impacted mandibular third molar (LM3) in a panoramic radiograph is important in surgical planning. The aim of this study was to develop and evaluate a computer-aided visualisation-based deep learning (DL) sy...

Deep learning with convolution neural network detecting mesiodens on panoramic radiographs: comparing four models.

Odontology
The aim of this study was to develop an optimal, simple, and lightweight deep learning convolutional neural network (CNN) model to detect the presence of mesiodens on panoramic radiographs. A total of 628 panoramic radiographs with and without mesiod...

Accuracy of automated forensic dental age estimation lab (F-DentEst Lab) on large Malaysian dataset.

Forensic science international
When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in ma...

Deep learning classification performance for diagnosing condylar osteoarthritis in patients with dentofacial deformities using panoramic temporomandibular joint projection images.

Oral radiology
OBJECTIVE: The present study aimed to assess the consistencies and performances of deep learning (DL) models in the diagnosis of condylar osteoarthritis (OA) among patients with dentofacial deformities using panoramic temporomandibular joint (TMJ) pr...