---
license: cc-by-4.0
task_categories:
  - image-segmentation
tags:
  - medical
  - ct
  - chest
  - lung
  - airway
  - segmentation
  - atm22
  - 3d
size_categories:
  - n<1K
---

# ATM22 — Airway Tree Modeling Challenge 2022 (re-mirror)

Re-hosted mirror of the **ATM22** challenge training set (Zhang et al.,
*Medical Image Analysis* 2023, arXiv:2303.05745), originally distributed
through the [ATM22 Grand Challenge](https://atm22.grand-challenge.org/).
This mirror rebuilds the data from the authors' own
[Zenodo re-publication](https://zenodo.org/records/6590745) under
CC BY 4.0, restructured into the same layout we use for KiTS23 / KiPA22 /
AbdomenCT1K / etc. so a single `Base3DDataset` subclass can load it.

## Composition

| Split | Cases | With mask |
|-------|------:|----------:|
| train | 299   | yes       |

Original challenge composition: 300 train + 50 val (image-only) + 150 test
(withheld). This mirror ships **train only** (300 cases minus 1 for
`ATM_164` whose label is misaligned with its corresponding image per
challenge errata = 299 usable cases). The val and test sets have no
public masks and so cannot be evaluated locally; refetch them from
Zenodo `imagesVal.rar` if you want inference-only inputs.

## File layout

```
dataset/ATM_001/
  imaging.nii.gz
  segmentation.nii.gz
...
dataset/ATM_500/
train.jsonl
README.md
```

`train.jsonl` lists one entry per case with `image`, `mask`, `label`,
`modality`, `dataset`, `official_split`, `patient_id` keys. Image/mask
paths are prefixed with `data/nii/ATM22/` so they slot directly into
the EasyMedSeg `Base3DDataset` `HF_JSONL_PREFIX` convention.

## Mask labels

Binary airway mask:

| Value | Class      |
|-------|------------|
| 0     | background |
| 1     | airway     |

The airway annotation includes trachea, main bronchi, lobar bronchi, and
segmental bronchi as one composite class (no branch-level subclasses in
the public release).

## License

CC BY 4.0, inherited from the upstream Zenodo mirror. The official
challenge organizers' research-only terms apply on top. Cite the
benchmark paper:

```bibtex
@article{zhang2023multi,
  title   = {Multi-site, multi-domain airway tree modeling (ATM'22):
             A public benchmark for pulmonary airway segmentation},
  author  = {Zhang, Minghui and Wu, Yangqian and Zhang, Hanxiao and others},
  journal = {Medical Image Analysis},
  year    = {2023},
  doi     = {10.1016/j.media.2023.102957}
}
```