[HTML][HTML] A review of deep learning in dentistry

C Huang, J Wang, S Wang, Y Zhang - Neurocomputing, 2023 - Elsevier
Oral diseases have a significant impact on human health, often going unnoticed in their
early stages. Deep learning, a promising field in artificial intelligence, has shown remarkable …

Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging

KF Hung, AWK Yeung, MM Bornstein… - Dentomaxillofacial …, 2023 - academic.oup.com
Personalized medicine refers to the tailoring of diagnostics and therapeutics to individuals
based on one's biological, social, and behavioral characteristics. While personalized dental …

Artificial intelligence and augmented reality for guided implant surgery planning: a proof of concept

FG Mangano, O Admakin, H Lerner, C Mangano - Journal of Dentistry, 2023 - Elsevier
Purpose To present a novel protocol for authentic three-dimensional (3D) planning of dental
implants, using artificial intelligence (AI) and augmented reality (AR). Methods The novel …

Tooth automatic segmentation from CBCT images: a systematic review

A Polizzi, V Quinzi, V Ronsivalle, P Venezia… - Clinical Oral …, 2023 - Springer
Objectives To describe the current state of the art regarding technological advances in full-
automatic tooth segmentation approaches from 3D cone-beam computed tomography …

Deep convolutional neural network-based automated segmentation of the maxillofacial complex from cone-beam computed tomography: A validation study

F Preda, N Morgan, A Van Gerven, F Nogueira-Reis… - Journal of Dentistry, 2022 - Elsevier
Objectives The present study investigated the accuracy, consistency, and time-efficiency of a
novel deep convolutional neural network (CNN) based model for the automated …

Analysis of deep learning techniques for dental informatics: a systematic literature review

S AbuSalim, N Zakaria, MR Islam, G Kumar, N Mokhtar… - Healthcare, 2022 - mdpi.com
Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study.
One of the major obstacles to the health care system's transformation is obtaining …

[HTML][HTML] Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study

BM Elgarba, S Van Aelst, A Swaity, N Morgan… - Journal of Dentistry, 2023 - Elsevier
Objectives To train and validate a cloud-based convolutional neural network (CNN) model
for automated segmentation (AS) of dental implant and attached prosthetic crown on cone …

[HTML][HTML] Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction

J Liu, J Hao, H Lin, W Pan, J Yang, Y Feng, G Wang… - Patterns, 2023 - cell.com
Summary High-fidelity three-dimensional (3D) models of tooth-bone structures are valuable
for virtual dental treatment planning; however, they require integrating data from cone-beam …

[HTML][HTML] Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images–A …

RC Fontenele, M do Nascimento Gerhardt, JC Pinto… - Journal of dentistry, 2022 - Elsevier
Objectives To assess the influence of dental fillings on the performance of an artificial
intelligence (AI)-driven tool for tooth segmentation on cone-beam computed tomography …

Convolutional neural network‐based automated maxillary alveolar bone segmentation on cone‐beam computed tomography images

RC Fontenele, MN Gerhardt, FF Picoli… - Clinical Oral …, 2023 - Wiley Online Library
Objectives To develop and assess the performance of a novel artificial intelligence (AI)‐
driven convolutional neural network (CNN)‐based tool for automated three‐dimensional …