| # VerSe – Vertebrae Labelling and Segmentation Benchmark |
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| ## License |
| **CC BY-SA 4.0** |
| [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/) |
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| ## Citation |
| Paper BibTeX: |
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| ```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} |
| } |
| ``` |
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| ## 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. |
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| **Challenge homepage**: https://verse2020.grand-challenge.org/ |
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| **Number of CT volumes**: 374 |
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| **CT Type**: Multi-detector CT (MDCT) |
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| **CT body coverage**: Spine (various fields of view) |
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| **Does the dataset include any ground truth annotations?**: Yes |
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| **Original GT annotation targets**: Vertebrae C1–L5, transitional T13 and L6 |
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| **Number of annotated CT volumes**: 374 |
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| **Annotator**: Automated algorithm + manual refinement |
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| **Acquisition centers**: - |
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| **Pathology/Disease**: Vertebral fractures, metallic implants, and foreign materials |
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| **Original dataset download link**: |
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| https://github.com/anjany/verse |
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| https://osf.io/4skx2/ |
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| **Original dataset format**: nifti |
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| ## Note |
| VerSe19 contains 160 scans and VerSe20 contains 319 scans; the merged dataset used here totals 374 scans. |
