Update README.md

README.md

@@ -1,3 +1,88 @@
----
-license: cc0-1.0
----
+---
+license: cc0-1.0
+language:
+- en
+- ru
+- kz
+pretty_name: "MAGIC-CT: Multiorgan Annotation and Grounded Image Captioning in CT for Cancer"
+tags:
+- medical-imaging
+- computed-tomography
+- cancer-detection
+- 3d-segmentation
+- multimodal
+- radiology
+---
+
+# MAGIC-CT: Multiorgan Annotation and Grounded Image Captioning in CT for Cancer
+
+## Description
+
+**MAGIC-CT** is a comprehensive, multimodal dataset designed to advance artificial intelligence in abdominal oncology. It addresses the critical need for resources that bridge the gap between radiological imaging and clinical language by pairing high-resolution 3D Computed Tomography (CT) scans with expert-authored radiology reports.
+
+The dataset includes 562 patients with various abdominal tumors, covering 7 distinct pathologies across 4 organs:
+*   **Liver:** Liver Cysts, Liver Cancer (Hepatocellular Carcinoma)
+*   **Lungs:** Lung Metastases, Lung Cancer
+*   **Kidneys:** Kidney Cysts, Renal Cancer
+*   **Pancreas:** Pancreatic Cancer
+
+Each patient case features at least one annotated CT scan with detailed 3D segmentation masks that delineate tumor boundaries and key anatomical structures. These visual data are paired with a radiologist-authored report that provides a comprehensive narrative of organ-specific findings and the overall abdominal status. With over 1,250 annotated lesions and 850 textual findings, MAGIC-CT offers the granular spatial-textual alignment required for training robust multimodal AI systems.
+
+This resource enables significant advancements in AI-driven tumor characterization, automated report generation, and metastasis tracking, with profound implications for the future of precision oncology.
+
+## Dataset Access
+
+The full MAGIC-CT dataset is hosted on Google Drive due to its large size. You can access and download it using the following link:
+
+**[Download the MAGIC-CT Dataset from Google Drive](https://drive.google.com/drive/folders/1SwR7A6OkW1DsgjSdcZTtmxBsa0lKSbpH?usp=drive_link)**
+
+### Dataset Structure
+
+The dataset is organized into three main folders: `scans`, `segmentations`, and `reports`.
+
+*   `/scans`: Contains all imaging data in anonymized `.nrrd` format.
+*   `/segmentations`: Contains the corresponding 3D segmentation masks, also in `.nrrd` format.
+*   `/reports`: Contains structured `.json` files with patient metadata and narrative reports in English (`en`), Russian (`ru`), and Kazakh (`kz`).
+
+An example of the `.json` report structure is as follows:
+```json
+{
+  "encrypted_patient_id": "abc12345",
+  "age": 65,
+  "gender": "male",
+  "screening_date": "2023-04-17",
+  "ru": {
+    "liver": "...",
+    "pancreas": "...",
+    "kidneys": "..."
+  },
+  "kz": {
+    "liver": "...",
+    "pancreas": "...",
+    "kidneys": "..."
+  },
+  "en": {
+    "liver": "The liver has a homogeneous structure; no focal lesions detected.",
+    "pancreas": "Mass identified in the pancreatic body, measuring 5.3×3.5 cm...",
+    "kidneys": "Small cortical cysts in both kidneys, no hydronephrosis."
+  }
+}
+```
+
+## Citation Information
+
+If you use the MAGIC-CT dataset in your research, please cite our paper:
+
+```bibtex
+@article{popov2025magicct,
+  title={MAGIC-CT: Multiorgan Annotation and Grounded Image Captioning in CT for Cancer},
+  author={Popov, Maxim and Iklassov, Zangir and Zhumabekov, Shakhnazar and and others},
+  journal={Nature Medicine (or relevant journal)},
+  year={2025},
+  publisher={Nature Publishing Group}
+}
+```
+
+---
+
+*This dataset was developed by the Department of Computer Science, School of Engineering and Digital Sciences at Nazarbayev University, Astana, Kazakhstan.*