Datasets:
File size: 2,911 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: sample_id
dtype: string
- name: subset
dtype: string
- name: labeled
dtype: bool
splits:
- name: a_pxi_labeled
num_examples: 850
- name: a_pxi_unlabeled
num_examples: 2650
- name: c_pxi_labeled
num_examples: 50
- name: c_pxi_unlabeled
num_examples: 450
configs:
- config_name: default
data_files:
- split: a_pxi_labeled
path: data/a_pxi_labeled-*
- split: a_pxi_unlabeled
path: data/a_pxi_unlabeled-*
- split: c_pxi_labeled
path: data/c_pxi_labeled-*
- split: c_pxi_unlabeled
path: data/c_pxi_unlabeled-*
license: cc-by-4.0
task_categories:
- image-segmentation
tags:
- medical-imaging
- dental
- panoramic-x-ray
- tooth-segmentation
- semi-supervised
pretty_name: STS-2D-Tooth
size_categories:
- 1K<n<10K
---
# 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)](https://doi.org/10.1038/s41597-024-04306-9)
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 |
Masks are 1-bit binary tooth-region masks at the same resolution as the source
image. Annotations were initialized manually on a 300-image seed by 20 trained
dental practitioners, refined by an R2 U-Net assistant model, and quality-vetted
by 6 dentists.
## Splits
- `a_pxi_labeled` (850) - adult panoramic X-rays with binary tooth masks
- `a_pxi_unlabeled` (2,650) - adult panoramic X-rays, no masks
- `c_pxi_labeled` (50) - paediatric panoramic X-rays with binary tooth masks
- `c_pxi_unlabeled` (450) - paediatric panoramic X-rays, no masks
For unlabeled splits the `mask` column is null.
## Citation
```bibtex
@article{wang2025sts,
title = {A multi-modal dental dataset for semi-supervised deep learning image segmentation},
author = {Wang, Yaqi and others},
journal = {Scientific Data},
volume = {12},
pages = {117},
year = {2025},
doi = {10.1038/s41597-024-04306-9}
}
@article{wang2024stschallenge,
title = {STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation},
author = {Wang, Yaqi and others},
journal = {arXiv:2407.13246},
year = {2024}
}
```
## License
CC-BY-4.0 (per the Zenodo release at
[zenodo.org/records/10597292](https://zenodo.org/records/10597292)).
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