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Our work with dental 3D models

Tooth segmentation from three dimensional scans of the dental arch

This study aimed to segment individual teeth from various dental arch morphologies in 3D intraoral scans using domain adaptation.

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Application of 3D neural networks and explainable AI to classify extent of caries

The purpose of this study was to investigate the difference in 3-dimensionsal (3D) model cavity preparations after International Caries Detection and Assessment System (ICDAS) classification performed by different practitioners and the subsequent influence on the ability of a deep learning model to predict cavity classification.

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An Application of 3D Vision Transformers and Explainable AI in Prosthetic Dentistry

To create and validate a transformer-based deep neural network architecture for classifying 3D scans of teeth for computer-assisted manufacturing and dental prosthetic rehabilitation

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A comparison of a handheld minicomputer and an external graphics processing unit in performing 3D intraoral scans

to compare the 3D intraoral scan accuracy and scan time of a small portable device and an eGPU with desktop-grade workstations.

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Influence of Intraoral Scanners, Operators, and Data Processing on Dimensional Accuracy of Dental Casts for Clinical Machine Learning

This study assessed the impact of intraoral scanner type, operator, and data augmentation on the dimensional accuracy of in vitro dental cast digital scans. It also evaluated the validation accuracy of an unsupervised machine-learning model trained with these scans.

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Using 3D neural networks and novel workflows in the dental prostheses fabrication process

This multiphase, invitro study developed and validated a 3-dimensional convolutional neural network (3D-CNN) to generate partial dental crowns (PDC) for use in restorative dentistry.

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