MedSAM2: Medical Segment Anything Model v2

Model Overview

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.

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 a comprehensive 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:

# 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

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.

Citations

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License

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Contact

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