| # AMOS (Multi-Modality Abdominal Multi-Organ Segmentation Challenge) |
|
|
| ## License |
| **CC BY 4.0** |
| [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/) |
|
|
| ## Citation |
| Paper BibTeX: |
|
|
| ```bibtex |
| @article{ji2022amos, |
| title={Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation}, |
| author={Ji, Yuanfeng and Bai, Haotian and Ge, Chongjian and Yang, Jie and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhanng, Lingyan and Ma, Wanling and Wan, Xiang and others}, |
| journal={Advances in neural information processing systems}, |
| volume={35}, |
| pages={36722--36732}, |
| year={2022} |
| } |
| ``` |
|
|
|
|
| ## Dataset description |
| AMOS is a large-scale abdominal multi-organ segmentation benchmark designed to advance clinical applications such as disease diagnosis and treatment planning. It contains 500 CT and 100 MRI scans from multi-center, multi-vendor, multi-modality, and multi-phase acquisitions, covering patients with a variety of abdominal diseases. Each case includes voxel-level annotations for 15 abdominal organs, enabling the development and fair comparison of versatile segmentation algorithms. |
|
|
| **Challenge homepage**: https://amos22.grand-challenge.org/ |
|
|
| **Number of CT volumes**: 200 |
|
|
| **Contrast**: Contrast and non-contrast |
|
|
| **CT body coverage**: Abdomen |
|
|
| **Does the dataset include any ground truth annotations?**: Yes |
|
|
| **Original GT annotation targets**: (15 abdominal organs) spleen, right kidney, left kidney, gallbladder, esophagus, liver, stomach, aorta, inferior vena cava, pancreas, right adrenal gland, left adrenal gland, duodenum, bladder, prostate/uterus |
|
|
| **Number of annotated CT volumes**: 200 |
|
|
| **Annotator**: AI + human refinement |
|
|
| **Acquisition centers**: Longgang District Central Hospital (SZ, CHINA) and Longgang District People's Hospital (SZ, CHINA). |
|
|
| **Pathology/Disease**: Patients diagnosed with abdominal tumors or other abnormalities; normal abdomen cases excluded |
|
|
| **Original dataset download link**: https://zenodo.org/records/7262581 |
|
|
| **Original dataset format**: nifti |
|
|
