Update README with model link and documentation

README.md

@@ -1,13 +1,53 @@
 ---
 title: Spleen Segmentation Demo
-emoji: 🐢
-colorFrom: pink
-colorTo: gray
+emoji: 🚀
+colorFrom: blue
+colorTo: green
 sdk: gradio
 sdk_version: 5.47.2
 app_file: app.py
 pinned: false
-short_description: CT spleen segmentation using MONAI/example_spleen_segmentati
+short_description: 3D spleen segmentation with MONAI
+models:
+  - MONAI/example_spleen_segmentation
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# CT Spleen Segmentation Demo
+
+This Space demonstrates 3D spleen segmentation from CT scans using the [MONAI/example_spleen_segmentation](https://huggingface.co/MONAI/example_spleen_segmentation) model.
+
+## Model Information
+
+- **Architecture**: UNet
+- **Input**: 3D CT images (96×96×96)
+- **Output**: Binary segmentation (spleen vs background)
+- **Performance**: Mean Dice Score = 0.96
+- **Training**: Trained on Medical Segmentation Decathlon Challenge 2018 dataset
+
+## How to Use
+
+1. Upload a CT scan in NIfTI format (.nii or .nii.gz)
+2. Click "Segment Spleen"
+3. View the segmentation overlay (middle slice visualization)
+4. Download the full 3D segmentation
+
+## Requirements
+
+- MONAI
+- PyTorch
+- nibabel
+- numpy
+- huggingface_hub
+
+## Citation
+
+If you use this model, please cite:
+
+```
+Xia, Yingda, et al. "3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training." 
+arXiv preprint arXiv:1811.12506 (2018).
+```
+
+## Disclaimer
+
+This is an example demonstration, not to be used for diagnostic purposes.