AIMC Topic: Radiography, Panoramic

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Dental implant brand and angle identification using deep neural networks.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Determining the brand and angle of an implant clinically or radiographically can be challenging. Whether artificial intelligence can assist is unclear.

Performance evaluation of deep learning models for the classification and identification of dental implants.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Dental implant systems can be identified using image classification deep learning. However, investigations on the accuracy of classifying and identifying implant design through an object detection model are lacking.

Robust automated teeth identification from dental radiographs using deep learning.

Journal of dentistry
OBJECTIVES: This study developed and validated a deep learning-based method to automatically segment and number teeth in panoramic radiographs across primary, mixed, and permanent dentitions.

Effect of data size on tooth numbering performance via artificial intelligence using panoramic radiographs.

Oral radiology
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.

Automated permanent tooth detection and numbering on panoramic radiograph using a deep learning approach.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to assess the performance of the deep learning (DL) model for automated tooth numbering in panoramic radiographs.

Federated vs Local vs Central Deep Learning of Tooth Segmentation on Panoramic Radiographs.

Journal of dentistry
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple data sources without directly sharing data. Due to the large amount of sensitive data in dentistry, FL may be particularly relevant...

Development of deep learning model and evaluation in real clinical practice of lingual mandibular bone depression (Stafne cyst) on panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any surgical treatment. It is sometimes confused with a cyst or another radiolucent pathologic lesion on ...

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...

Developing deep learning methods for classification of teeth in dental panoramic radiography.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: We aimed to develop an artificial intelligence-based clinical dental decision-support system using deep-learning methods to reduce diagnostic interpretation error and time and increase the effectiveness of dental treatment and classificat...

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).