AIMC Topic: Tooth

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Optimization technique combined with deep learning method for teeth recognition in dental panoramic radiographs.

Scientific reports
Computer-assisted analysis of dental radiograph in dentistry is getting increasing attention from the researchers in recent years. This is mainly because it can successfully reduce human-made error due to stress, fatigue or lack of experience. Furthe...

Artificial intelligence provides greater accuracy in the classification of modern and ancient bone surface modifications.

Scientific reports
Bone surface modifications are foundational to the correct identification of hominin butchery traces in the archaeological record. Until present, no analytical technique existed that could provide objectivity, high accuracy, and an estimate of probab...

Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs.

Clinical oral investigations
OBJECTIVE: To evaluate the performance of a new artificial intelligence (AI)-driven tool for tooth detection and segmentation on panoramic radiographs.

Personal identification with orthopantomography using simple convolutional neural networks: a preliminary study.

Scientific reports
Forensic dental examination has played an important role in personal identification (PI). However, PI has essentially been based on traditional visual comparisons of ante- and postmortem dental records and radiographs, and there is no globally accept...

Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: To evaluate a fully deep learning mask region-based convolutional neural network (R-CNN) method for automated tooth segmentation using individual annotation of panoramic radiographs.

Convolutional neural networks for dental image diagnostics: A scoping review.

Journal of dentistry
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.

Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network.

Medical physics
PURPOSE: In order to attain anatomical models, surgical guides and implants for computer-assisted surgery, accurate segmentation of bony structures in cone-beam computed tomography (CBCT) scans is required. However, this image segmentation step is of...

Deep Learning for the Radiographic Detection of Apical Lesions.

Journal of endodontics
INTRODUCTION: We applied deep convolutional neural networks (CNNs) to detect apical lesions (ALs) on panoramic dental radiographs.

A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films.

Scientific reports
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...

Tooth detection and numbering in panoramic radiographs using convolutional neural networks.

Dento maxillo facial radiology
OBJECTIVES: Analysis of dental radiographs is an important part of the diagnostic process in daily clinical practice. Interpretation by an expert includes teeth detection and numbering. In this project, a novel solution based on convolutional neural ...