[HTML][HTML] 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 …

Deep learning-based tooth segmentation methods in medical imaging: A review

X Chen, N Ma, T Xu, C Xu - … Part H: Journal of Engineering in …, 2024‏ - journals.sagepub.com
Deep learning approaches for tooth segmentation employ convolutional neural networks
(CNNs) or Transformers to derive tooth feature maps from extensive training datasets. Tooth …

[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 …

DBGANet: dual-branch geometric attention network for accurate 3D tooth segmentation

Z Lin, Z He, X Wang, B Zhang, C Liu… - … on Circuits and …, 2023‏ - ieeexplore.ieee.org
Accurate segmentation of 3D dental models derived from intra-oral scanners (IOS) is one of
the key steps in many digital dental applications such as orthodontics and implants …

Darch: Dental arch prior-assisted 3d tooth instance segmentation with weak annotations

L Qiu, C Ye, P Chen, Y Liu, X Han… - Proceedings of the …, 2022‏ - openaccess.thecvf.com
Automatic tooth instance segmentation on 3D dental models is a fundamental task for
computer-aided orthodontic treatments. Existing learning-based methods rely heavily on …

GRAB-Net: Graph-based boundary-aware network for medical point cloud segmentation

Y Liu, W Li, J Liu, H Chen… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Point cloud segmentation is fundamental in many medical applications, such as aneurysm
clip** and orthodontic planning. Recent methods mainly focus on designing powerful …

Semantic graph attention with explicit anatomical association modeling for tooth segmentation from CBCT images

P Li, Y Liu, Z Cui, F Yang, Y Zhao… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Accurate tooth identification and delineation in dental CBCT images are essential in clinical
oral diagnosis and treatment. Teeth are positioned in the alveolar bone in a particular order …

Two-stream graph convolutional network for intra-oral scanner image segmentation

Y Zhao, L Zhang, Y Liu, D Meng, Z Cui… - … on Medical Imaging, 2021‏ - ieeexplore.ieee.org
Precise segmentation of teeth from intra-oral scanner images is an essential task in
computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based …

NKUT: dataset and benchmark for pediatric mandibular wisdom teeth segmentation

Z Zhou, Y Chen, A He, X Que, K Wang… - IEEE Journal of …, 2024‏ - ieeexplore.ieee.org
Germectomy is a common surgery in pediatric dentistry to prevent the potential dangers
caused by impacted mandibular wisdom teeth. Segmentation of mandibular wisdom teeth is …

Self-supervised learning with masked autoencoders for teeth segmentation from intra-oral 3d scans

A Almalki, LJ Latecki - Proceedings of the IEEE/CVF Winter …, 2024‏ - openaccess.thecvf.com
In modern dentistry, teeth localization, segmentation, and labeling from intra-oral 3D scans
are crucial for improving dental diagnostics, treatment planning, and population-based …