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 …

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 …

[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 …

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 …

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 …

Recent advancement in learning methodology for segmenting brain tumor from magnetic resonance imaging-a review

SG Domadia, FN Thakkar, MA Ardeshana - Multimedia Tools and …, 2023 - Springer
Glioblastomata are the most generally perceived fundamental brain malignant tumors
known as Gliomas, with different shape, size & sub regions. It is hard to segment all three …

Robust hybrid learning for automatic teeth segmentation and labeling on 3D dental models

S Zhuang, G Wei, Z Cui, Y Zhou - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic teeth segmentation and labeling on dental models are basic tasks in computer-
aided dentistry. Many existing works can achieve promising results in teeth segmentation …

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
clipping and orthodontic planning. Recent methods mainly focus on designing powerful …

Heterogeneous data fusion and loss function design for tooth point cloud segmentation

D Liu, Y Tian, Y Zhang, J Gelernter, X Wang - Neural Computing and …, 2022 - Springer
Tooth point cloud segmentation plays an important role in the digital dentistry, and has
received much attention in the past decade. Recently, methods based on the graph neural …