Upload README_0009_abdomenct1k.md

0009_abdomenct1k/README_0009_abdomenct1k.md

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+# 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