TSegNet: An efficient and accurate tooth segmentation network on 3D dental model
Automatic and accurate segmentation of dental models is a fundamental task in computer-
aided dentistry. Previous methods can achieve satisfactory segmentation results on normal …
aided dentistry. Previous methods can achieve satisfactory segmentation results on normal …
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 …
the key steps in many digital dental applications such as orthodontics and implants …
Deep multi-scale mesh feature learning for automated labeling of raw dental surfaces from 3D intraoral scanners
Precisely labeling teeth on digitalized 3D dental surface models is the precondition for tooth
position rearrangements in orthodontic treatment planning. However, it is a challenging task …
position rearrangements in orthodontic treatment planning. However, it is a challenging task …
Two-stage mesh deep learning for automated tooth segmentation and landmark localization on 3D intraoral scans
Accurately segmenting teeth and identifying the corresponding anatomical landmarks on
dental mesh models are essential in computer-aided orthodontic treatment. Manually …
dental mesh models are essential in computer-aided orthodontic treatment. Manually …
Deep learning on implicit neural representations of shapes
Implicit Neural Representations (INRs) have emerged in the last few years as a powerful tool
to encode continuously a variety of different signals like images, videos, audio and 3D …
to encode continuously a variety of different signals like images, videos, audio and 3D …
Tsgcnet: Discriminative geometric feature learning with two-stream graph convolutional network for 3d dental model segmentation
The ability to segment teeth precisely from digitized 3D dental models is an essential task in
computer-aided orthodontic surgical planning. To date, deep learning based methods have …
computer-aided orthodontic surgical planning. To date, deep learning based methods have …
Two-stream graph convolutional network for intra-oral scanner image segmentation
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 …
computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based …
MeshCLIP: Efficient cross-modal information processing for 3D mesh data in zero/few-shot learning
Y Song, N Liang, Q Guo, J Dai, J Bai, F He - Information Processing & …, 2023 - Elsevier
Abstract Text, 2D, and 3D information are crucial information representations in modern
science and management disciplines. However, complex and irregular 3D data produce …
science and management disciplines. However, complex and irregular 3D data produce …
Toward clinically applicable 3-dimensional tooth segmentation via deep learning
Digital dentistry plays a pivotal role in dental health care. A critical step in many digital dental
systems is to accurately delineate individual teeth and the gingiva in the 3-dimension …
systems is to accurately delineate individual teeth and the gingiva in the 3-dimension …
Subdivision-based mesh convolution networks
Convolutionalneural networks (CNNs) have made great breakthroughs in two-dimensional
(2D) computer vision. However, their irregular structure makes it hard to harness the …
(2D) computer vision. However, their irregular structure makes it hard to harness the …