LUNA25_ts_seg / README.md
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---
title: "LUNA25_TS_seg"
license: cc-by-nc-sa-4.0
configs:
- config_name: metadata
data_files: "metadata.csv"
---
# LUNA25 TS Segmentations
The [LUNA25 challenge](https://luna25.grand-challenge.org/) serves as a benchmark for evaluating lung nodule detection in low-dose CT scans. This repository includes segmentations generated using [TotalSegmentator](https://github.com/wasserth/TotalSegmentator) for the `total`, `lung_vessels`, and `lung_nodules` tasks. Note: Segmentation volumes have not been independently verified and are supplied "as is".
## Steps to recreate
1. Use `scripts/convert_nifti.py` and `scripts/convert_nifti.sh` to convert LUNA25 `.mha` files to `.nii.gz`.
2. Install [TotalSegmentator](https://github.com/wasserth/TotalSegmentator).
3. Run TS segmentation scripts (written for parallel execution):
- `scripts/ts_total.sh`
- `scripts/ts_lung_vessels.sh`
- `scripts/ts_lung_nodules.sh`
4. Run `scripts/get_metadata.py` to get metadata for detected lung nodules.
```text
Installation Info:
- Date installed: Mar 6, 2025.
- Python version: 3.9.15
- TotalSegmentator version: 2.7.0
```
For full list of package versions, see [requirements.txt](requirements.txt).
## Citation
```text
@misc{luna25,
title={{LUNA25: LUng Nodule Analysis Challenge}},
author={{Grand-Challenge.org}},
year={2025}
howpublished={\url{https://luna25.grand-challenge.org/}},
}
@article{wasserthal2023totalsegmentator,
title={TotalSegmentator: robust segmentation of 104 anatomic structures in CT images},
author={Wasserthal, Jakob and Breit, Hanns-Christian and Meyer, Manfred T and Pradella, Maurice and Hinck, Daniel and Sauter, Alexander W and Heye, Tobias and Boll, Daniel T and Cyriac, Joshy and Yang, Shan and others},
journal={Radiology: Artificial Intelligence},
volume={5},
number={5},
pages={e230024},
year={2023},
publisher={Radiological Society of North America}
}
@article{poletti2022automated,
title={Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia},
author={Poletti, Julien and Bach, Michael and Yang, Shan and Sexauer, Raphael and Stieltjes, Bram and Rotzinger, David C and Bremerich, Jens and Sauter, Alexander Walter and Weikert, Thomas},
journal={European Journal of Radiology},
volume={150},
pages={110259},
year={2022},
publisher={Elsevier}
}
```