Upload README_0008_ctorg.md

0008_ctorg/README_0008_ctorg.md

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+# CT-ORG: Multiple Organ Segmentation in CT
+
+## License
+**CC BY 3.0**  
+[Creative Commons Attribution 3.0 License](https://creativecommons.org/licenses/by/3.0/)
+
+## Citation
+Paper BibTeX:
+```bibtex
+@article{rister2020ct,
+  title={CT-ORG, a new dataset for multiple organ segmentation in computed tomography},
+  author={Rister, Blaine and Yi, Darvin and Shivakumar, Kaushik and Nobashi, Tomomi and Rubin, Daniel L},
+  journal={Scientific Data},
+  volume={7},
+  number={1},
+  pages={381},
+  year={2020},
+  publisher={Nature Publishing Group UK London}
+}
+```
+
+Dataset:
+
+```bibtex
+Rister, B., Shivakumar, K., Nobashi, T., & Rubin, D. L. (2019). CT-ORG: A Dataset of CT Volumes With Multiple Organ Segmentations (Version 1) [dataset]. The Cancer Imaging Archive.  DOI: 10.7937/tcia.2019.tt7f4v7o
+```
+
+
+## Dataset description
+CT-ORG contains 140 CT scans from diverse sources, each with 3D segmentations of five organs, and brain labels in some cases. The dataset covers a wide range of imaging conditions and includes both benign and malignant liver lesions, as well as metastatic disease in bones and lungs, providing a challenging benchmark for multi-class organ segmentation.
+
+**Number of CT volumes**: 140
+
+**Contrast**: Both contrast-enhanced and non-contrast; includes PET-CT derived scans
+
+**CT body coverage**: Abdominal and full-body
+
+**Does the dataset include any ground truth annotations?**: Yes
+
+**Original GT annotation targets**: Liver, urinary bladder, lungs, kidneys, bone
+
+**Number of annotated CT volumes**: 140
+
+**Annotator**: Human (lungs and bones partly from morphological algorithms)
+
+**Acquisition centers**: Multiple global institutions, Ludwig Maxmilian University of Munich, Radboud University Medical Center of Nijmegen, Poly-technique & CHUM Research Center Montreal, Tel Aviv University, Sheba Medical Center, IRCAD Institute Strasbourg and Hebrew University of Jerusalem. The PET-CT images all derive from Stanford Healthcare.
+
+**Pathology/Disease**: Benign and malignant liver lesions, metastatic disease in bones and lungs
+
+**Original dataset download link**: https://www.cancerimagingarchive.net/collection/ct-org/
+
+**Original dataset format**: nifti