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0014_learn2reg/README_0014_learn2reg.md

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+# Learn2Reg – Abdomen MR-CT (TCIA Subset)
+
+## License
+Because Learn2Reg sourced images from different datasets and here we only used the TCIA-relevant subset, the license is as follows:  
+TCIA (TCGA-KIRC, TCGA-KIRP, TCGA-LIHC): [TCIA Data Usage Policy](https://www.cancerimagingarchive.net/data-usage-policies/) and [Creative Commons Attribution 3.0 Unported License](https://creativecommons.org/licenses/by/3.0/).
+
+## Citation
+Paper BibTeX:
+
+```bibtex
+@article{hering2022learn2reg,
+  title={Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning},
+  author={Hering, Alessa and Hansen, Lasse and Mok, Tony CW and Chung, Albert CS and Siebert, Hanna and H{\"a}ger, Stephanie and Lange, Annkristin and Kuckertz, Sven and Heldmann, Stefan and Shao, Wei and others},
+  journal={IEEE Transactions on Medical Imaging},
+  volume={42},
+  number={3},
+  pages={697--712},
+  year={2022},
+  publisher={IEEE}
+}
+```
+
+
+## Dataset description
+The Learn2Reg challenge provides datasets, annotations, and open-source evaluation code for developing and benchmarking medical image registration methods. The Abdomen MR-CT task includes CT scans with organ labels to support multi-modal abdominal image registration research.
+
+**Challenge homepage**: https://learn2reg.grand-challenge.org/learn2reg-2025/
+
+**Number of CT volumes**: 16
+
+**Contrast**: -
+
+**CT body coverage**: Abdomen
+
+**Does the dataset include any ground truth annotations?**: Yes
+
+**Original GT annotation targets**: Liver, spleen, right kidney, left kidney
+
+**Number of annotated CT volumes**: 8
+
+**Annotator**: Human
+
+**Acquisition centers**: -
+
+**Pathology/Disease**: -
+
+**Original dataset download link**: (Task "Abdomen MR-CT") https://learn2reg.grand-challenge.org/Datasets/
+
+**Original dataset format**: nifti
+
+## Note
+This subset contains 16 TCIA images from the Abdomen MR-CT task (sources: TCGA-KIRC, TCGA-KIRP, TCGA-LIHC), corresponding to imagesTr/ and imagesTs/ cases AbdomenMRCT_0001_0001 to AbdomenMRCT_0016_0001. Our internal IDs (learn2reg_img000x_tcia) do not match the original 1–16 numbering.