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# 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. |