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- # MedSAM2
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- - `MedSAM2_2411.pt`: The based model trained in Nov. 2024
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- - `MedSAM2_US_Heart.pt`: Fine-tuned model for heart ultrasound video segmentation
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- - `MedSAM2_MRI_LiverLesion.pt`: Fine-tuned model for liver lesion MRI segmentation
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- - `MedSAM2_CTLesion.pt`: Fine-tuned model for CT lesion segmentation
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- - `MedSAM2_latest.pt` (recommended): Latest model trained on the combination of existing public datasets and newly annotated datasets
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # MedSAM2: Medical Segment Anything Model v2
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+
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+ ## Model Overview
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+ MedSAM2 is an advanced segmentation model tailored for medical imaging applications. Built upon the foundation of the Segment Anything Model (SAM) architecture, MedSAM2 has been specifically adapted and fine-tuned for various medical imaging modalities including CT, MRI, and ultrasound.
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+
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+ ## Available Models
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+
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+ - **MedSAM2_2411.pt**: Base model trained in November 2024
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+ - **MedSAM2_US_Heart.pt**: Fine-tuned model specialized for heart ultrasound video segmentation
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+ - **MedSAM2_MRI_LiverLesion.pt**: Fine-tuned model for liver lesion segmentation in MRI scans
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+ - **MedSAM2_CTLesion.pt**: Fine-tuned model for general lesion segmentation in CT scans
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+ - **MedSAM2_latest.pt** (recommended): Latest version trained on a comprehensive combination of public datasets and newly annotated medical imaging data
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+
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+ ## Downloading Models
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+
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+ ### Option 1: Download individual models
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+ You can download the models directly from the Hugging Face repository:
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+
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+ ```python
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+ # Using huggingface_hub
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+ from huggingface_hub import hf_hub_download
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+
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+ # Download the recommended latest model
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+ model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_latest.pt")
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+
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+ # Or download a specific fine-tuned model
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+ heart_us_model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_US_Heart.pt")
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+ liver_model_path = hf_hub_download(repo_id="wanglab/MedSAM2", filename="MedSAM2_MRI_LiverLesion.pt")
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+ ```
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+
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+ ### Option 2: Download all models to a specific folder
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+ ```python
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+ from huggingface_hub import hf_hub_download
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+ import os
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+
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+ # Create checkpoints directory if it doesn't exist
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+ os.makedirs("checkpoints", exist_ok=True)
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+
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+ # List of model filenames
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+ model_files = [
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+ "MedSAM2_2411.pt",
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+ "MedSAM2_US_Heart.pt",
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+ "MedSAM2_MRI_LiverLesion.pt",
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+ "MedSAM2_CTLesion.pt",
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+ "MedSAM2_latest.pt"
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+ ]
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+
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+ # Download all models
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+ for model_file in model_files:
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+ local_path = os.path.join("checkpoints", model_file)
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+ hf_hub_download(
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+ repo_id="wanglab/MedSAM2",
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+ filename=model_file,
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+ local_dir="checkpoints",
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+ local_dir_use_symlinks=False
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+ )
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+ print(f"Downloaded {model_file} to {local_path}")
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+ ```
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+
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+ Alternatively, you can manually download the models from the [Hugging Face repository page](https://huggingface.co/wanglab/MedSAM2).
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+
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+
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+
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+ ## Citations
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+
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+ ```
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+ # Citation information will be added later
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+ ```
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+
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+ ## License
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+
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+ # License information will be added later
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+
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+ ## Contact
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+
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+ # Contact information will be added later