datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
STS-3D-Tooth
STS-3D-Tooth
The 3D Cone-Beam CT (CBCT) subset of the STS (Semi-supervised Teeth
Segmentation) multi-modal dental dataset, as released in
Wang et al., Scientific Data 12, 117 (2025)
and used in the MICCAI 2023/2024 STS Challenges.
The companion 2D panoramic X-ray subset is hosted at
Angelou0516/STS-2D-Tooth.
Dataset Summary
Field
Details
Modality
Cone-Beam CT (CBCT), NIfTI (.nii.gz)
Body Part
Teeth (32 permanent teeth, FDI numbering)
Volumes
371… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/STS-3D-Tooth.STS-2D-Tooth
STS-2D-Tooth
The 2D panoramic dental X-ray subset of the STS (Semi-supervised Teeth
Segmentation) multi-modal dataset, as released in
Wang et al., Scientific Data 12, 117 (2025)
and used in the MICCAI 2023 STS Challenge.
Composition
4,000 panoramic X-ray images (PNG, 640x320, 3-channel grayscale-as-RGB) split
across two demographic subsets:
Subset
Total
Labeled
Unlabeled
A-PXI (adult)
3,500
850
2,650
C-PXI (child)
500
50
450
Total
4,000
900
3,100… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/STS-2D-Tooth.Tooth-Agenesis-6_Types
Tooth-Agenesis-6_Types
This dataset contains labeled dental images intended for training machine learning models on the classification of six different oral health conditions. It is designed for image classification tasks, specifically targeting types of tooth agenesis and other related dental conditions.
Dataset Summary
Total Images: 12,320
Format: Parquet
Modality: Image
Split: train only
Size: 183 MB
Language: English
License: Apache 2.0
Labels
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/strangerguardhf/Tooth-Agenesis-6_Types.panoramic_x-ray_tooth_v2panoramic_x-ray_tooth