AIMC Topic: Age Determination by Teeth

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OPG-based dental age estimation using a data-technical exploration of deep learning techniques.

Journal of forensic sciences
Dental age estimation, a cornerstone in forensic age assessment, has been extensively tried and tested, yet manual methods are impeded by tedium and interobserver variability. Automated approaches using deep transfer learning encounter challenges lik...

Resolving the non-uniformity in the feature space of age estimation: A deep learning model based on feature clusters of panoramic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Age estimation is important in forensics, and numerous techniques have been investigated to estimate age based on various parts of the body. Among them, dental tissue is considered reliable for estimating age as it is less influenced by external fact...

A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches.

International journal of legal medicine
Dental radiographies have been used for many decades for estimating the chronological age, with a view to forensic identification, migration flow control, or assessment of dental development, among others. This study aims to analyse the current appli...

Age determination on panoramic radiographs using the Kvaal method with the aid of artificial intelligence.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to assess and compare age estimation on panoramic radiography using the Kvaal method and machine learning (ML).

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M.

International journal of environmental research and public health
Expert determination of the third molar maturity index (I3M) constitutes one of the most common approaches for dental age estimation. This work aimed to investigate the technical feasibility of creating a decision-making tool based on I3M to support ...

Variational autoencoder-based estimation of chronological age and changes in morphological features of teeth.

Scientific reports
This study led to the development of a variational autoencoder (VAE) for estimating the chronological age of subjects using feature values extracted from their teeth. Further, it determined how given teeth images affected the estimation accuracy. The...

Accurate age classification using manual method and deep convolutional neural network based on orthopantomogram images.

International journal of legal medicine
Age estimation is an important challenge in many fields, including immigrant identification, legal requirements, and clinical treatments. Deep learning techniques have been applied for age estimation recently but lacking performance comparison betwee...

Age-group determination of living individuals using first molar images based on artificial intelligence.

Scientific reports
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...

Comparison of different machine learning approaches to predict dental age using Demirjian's staging approach.

International journal of legal medicine
CONTEXT: Dental age, one of the indicators of biological age, is inferred by radiological methods. Two of the most commonly used methods are using Demirjian's radiographic stages of permanent teeth excluding the third molar (Demirjian's and Willems' ...

Application and performance of artificial intelligence technology in forensic odontology - A systematic review.

Legal medicine (Tokyo, Japan)
Forensic odontology (FO) mainly deals with the identification of the individual through the remains, which mainly includes teeth and jawbones. Artificial intelligence (AI) technology has proven to be a breakthrough in providing reliable information i...