Datasets:
File size: 1,859 Bytes
45f74bc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
# AbdomenCT-1K
## License
**CC BY 4.0**
[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/)
## Citation
Paper BibTeX:
```bibtex
@article{ma2021abdomenct,
title={Abdomenct-1k: Is abdominal organ segmentation a solved problem?},
author={Ma, Jun and Zhang, Yao and Gu, Song and Zhu, Cheng and Ge, Cheng and Zhang, Yichi and An, Xingle and Wang, Congcong and Wang, Qiyuan and Liu, Xin and others},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={44},
number={10},
pages={6695--6714},
year={2021},
publisher={IEEE}
}
```
## Dataset description
AbdomenCT-1K is a large, diverse abdominal CT organ segmentation dataset with over 1,000 scans from 12 medical centers, covering multiple phases, vendors, and diseases. It serves as a benchmark to reveal and address the limited generalization of state-of-the-art methods, providing tasks for fully, semi-, weakly supervised, and continual learning research.
**Challenge homepage**: https://abdomenct-1k-fully-supervised-learning.grand-challenge.org/
**Number of CT volumes**: 1062
**Contrast**: Contrast-enhanced (multi-phase: plain, arterial, portal)
**CT body coverage**: Abdomen
**Does the dataset include any ground truth annotations?**: Yes
**Original GT annotation targets**: Liver, spleen, kidney, pancreas
**Number of annotated CT volumes**: 1000
**Annotator**: Initial model + manual refinement
**Acquisition centers**: 12 medical centers
**Pathology/Disease**: Lesions in one or more labeled organs, including benign/malignant liver lesions and cancers of the pancreas, colon, and liver
**Original dataset download link**:
Part 1: https://zenodo.org/records/5903099
Part 2: https://zenodo.org/records/5903846
Part 3: https://zenodo.org/records/5903769
**Original dataset format**: nifti
|