0010_verse/README_0010_verse.md

# VerSe – Vertebrae Labelling and Segmentation Benchmark

## License
**CC BY-SA 4.0**  
[Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/)

## Citation
Paper BibTeX:

```bibtex
@article{sekuboyina2021verse,
  title={VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images},
  author={Sekuboyina, Anjany and Husseini, Malek E and Bayat, Amirhossein and L{\"o}ffler, Maximilian and Liebl, Hans and Li, Hongwei and Tetteh, Giles and Kuka{\v{c}}ka, Jan and Payer, Christian and {\v{S}}tern, Darko and others},
  journal={Medical image analysis},
  volume={73},
  pages={102166},
  year={2021},
  publisher={Elsevier}
}
```


## Dataset description
The VerSe benchmark, introduced at MICCAI 2019 and 2020, provides multi-detector CT scans for vertebrae labelling and segmentation. It includes 374 scans with over 4,500 vertebrae annotated using a human–machine hybrid approach, enabling the development and evaluation of algorithms across diverse anatomy and acquisition protocols.

**Challenge homepage**: https://verse2020.grand-challenge.org/

**Number of CT volumes**: 374

**CT Type**: Multi-detector CT (MDCT)

**CT body coverage**: Spine (various fields of view)

**Does the dataset include any ground truth annotations?**: Yes

**Original GT annotation targets**: Vertebrae C1–L5, transitional T13 and L6

**Number of annotated CT volumes**: 374

**Annotator**: Automated algorithm + manual refinement

**Acquisition centers**: -

**Pathology/Disease**: Vertebral fractures, metallic implants, and foreign materials

**Original dataset download link**: 

https://github.com/anjany/verse 

https://osf.io/4skx2/

**Original dataset format**: nifti

## Note
VerSe19 contains 160 scans and VerSe20 contains 319 scans; the merged dataset used here totals 374 scans.