Add removed sections (#2)

- Add removed sections (05818554bc41fb7f01e94d9dbee51c30472116cb)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -75,8 +75,78 @@ tags:
 - Versatile segmentation capability across diverse organs and pathologies
 - Extensive user studies in large-scale lesion and video datasets demonstrate that MedSAM2 substantially facilitates annotation workflows
 
-
 ## Model Overview
 MedSAM2 is a promptable segmentation segmentation model tailored for medical imaging applications. Built upon the foundation of the [Segment Anything Model (SAM) 2.1](https://github.com/facebookresearch/sam2), MedSAM2 has been specifically adapted and fine-tuned for various 3D medical images and videos.
 
-<!-- rest of the model card -->
+## Available Models
+
+- **MedSAM2_2411.pt**: Base model trained in November 2024
+- **MedSAM2_US_Heart.pt**: Fine-tuned model specialized for heart ultrasound video segmentation
+- **MedSAM2_MRI_LiverLesion.pt**: Fine-tuned model for liver lesion segmentation in MRI scans
+- **MedSAM2_CTLesion.pt**: Fine-tuned model for general lesion segmentation in CT scans
+- **MedSAM2_latest.pt** (recommended): Latest version trained on the combination of public datasets and newly annotated medical imaging data
+
+## Downloading Models
+
+### Option 1: Download individual models
+You can download the models directly from the Hugging Face repository:
+
+```python
+# Using huggingface_hub
+from huggingface_hub import hf_hub_download
+
+# Download the recommended latest model
+model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_latest.pt")
+
+# Or download a specific fine-tuned model
+heart_us_model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_US_Heart.pt")
+liver_model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_MRI_LiverLesion.pt")
+```
+
+### Option 2: Download all models to a specific folder
+```python
+from huggingface_hub import hf_hub_download
+import os
+
+# Create checkpoints directory if it doesn't exist
+os.makedirs("checkpoints", exist_ok=True)
+
+# List of model filenames
+model_files = [
+    "MedSAM2_2411.pt",
+    "MedSAM2_US_Heart.pt",
+    "MedSAM2_MRI_LiverLesion.pt",
+    "MedSAM2_CTLesion.pt",
+    "MedSAM2_latest.pt"
+]
+
+# Download all models
+for model_file in model_files:
+    local_path = os.path.join("checkpoints", model_file)
+    hf_hub_download(
+        repo_id="wanglab/MedSAM2",
+        filename=model_file,
+        local_dir="checkpoints",
+        local_dir_use_symlinks=False
+    )
+    print(f"Downloaded {model_file} to {local_path}")
+```
+
+Alternatively, you can manually download the models from the [Hugging Face repository page](https://huggingface.co/wanglab/MedSAM2).
+
+
+
+## Citations
+
+```
+@article{MedSAM2,
+    title={MedSAM2: Segment Anything in 3D Medical Images and Videos},
+    author={Ma, Jun and Yang, Zongxin and Kim, Sumin and Chen, Bihui and Baharoon, Mohammed and Fallahpour, Adibvafa and Asakereh, Reza and Lyu, Hongwei and Wang, Bo},
+    journal={arXiv preprint arXiv:2504.03600},
+    year={2025}
+}
+```
+
+## License
+
+The model weights can only be used for research and education purposes.