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Tooth

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Artificial neural networks and geometric morphometric methods as a means for classification: A case-study using teeth from Carcharhinus sp. (Carcharhinidae).

Journal of morphology
Over the past few decades, geometric morphometric methods have become increasingly popular and powerful tools to describe morphological data while over the same period artificial neural networks have had a similar rise in the classification of specim...

Artificial Neural Networks as a powerful numerical tool to classify specific features of a tooth based on 3D scan data.

Computers in biology and medicine
Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image ...

Classification of teeth in cone-beam CT using deep convolutional neural network.

Computers in biology and medicine
Dental records play an important role in forensic identification. To this end, postmortem dental findings and teeth conditions are recorded in a dental chart and compared with those of antemortem records. However, most dentists are inexperienced at r...

An Automatic Segmentation and Classification Framework Based on PCNN Model for Single Tooth in MicroCT Images.

PloS one
Accurate segmentation and classification of different anatomical structures of teeth from medical images plays an essential role in many clinical applications. Usually, the anatomical structures of teeth are manually labelled by experienced clinical ...

Automated tooth segmentation in magnetic resonance scans using deep learning - A pilot study.

Dento maxillo facial radiology
OBJECTIVES: The main objective was to develop and evaluate an artificial intelligence model for tooth segmentation in magnetic resonance (MR) scans.

[Tooth segmentation and identification on cone-beam computed tomography with convolutional neural network based on spatial embedding information].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To propose a novel neural network to achieve tooth instance segmentation and recognition based on cone-beam computed tomography (CBCT) voxel data.

[Accuracy of tooth segmentation algorithm based on deep learning].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: The established automatic AI tooth segmentation algorithm was used to achieve rapid and automatic tooth segmentation from CBCT images. The three-dimensional data obtained by oral scanning of real isolated teeth were used as the gold standard...

Adolescents and Children Age Estimation Using Machine Learning Based on Pulp and Tooth Volumes on CBCT Images.

Fa yi xue za zhi
OBJECTIVES: To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography (CBCT) images, and to co...

Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis.

Dento maxillo facial radiology
OBJECTIVES: Improved tools based on deep learning can be used to accurately number and identify teeth. This study aims to review the use of deep learning in tooth numbering and identification.