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Medical SAM3

Medical SAM3 is a foundation model for universal prompt-driven medical image segmentation, obtained by fully fine-tuning SAM3 on large-scale, heterogeneous 2D and 3D medical imaging datasets with paired segmentation...

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17.7 MB–9.59 GB
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vRevision 716c9e1
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Nov 1, 2026
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Hugging Face

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Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation

Medical SAM3 is a foundation model for universal prompt-driven medical image segmentation, obtained by fully fine-tuning SAM3 on large-scale, heterogeneous 2D and 3D medical imaging datasets with paired segmentation masks and text prompts.

Introduction

Promptable segmentation foundation models such as SAM3 have demonstrated strong generalization capabilities through interactive and concept-based prompting. However, their direct applicability to medical image segmentation remains limited by severe domain shifts.

By fine-tuning SAM3's model parameters on 33 datasets spanning 10 medical imaging modalities, Medical SAM3 acquires robust domain-specific representations while preserving prompt-driven flexibility. Experiments across organs, imaging modalities, and dimensionalities demonstrate consistent and significant performance gains.

Citation

@article{jiang2026medicalsam3,
  title={Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation},
  author={Jiang, Chongcong and Ding, Tianxingjian and Song, Chuhan and Tu, Jiachen and Yan, Ziyang and Shao, Yihua and Wang, Zhenyi and Shang, Yuzhang and Han, Tianyu and Tian, Yu},
  journal={arXiv preprint arXiv:2601.10880},
  year={2026},
  url={https://arxiv.org/abs/2601.10880}
}

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Hugging FacePrimaryVersion 716c9e1fb70edbdbbe65526b781e3a60f382d6cc
huggingface.co/ChongCong/Medical-SAM3/tree/716c9e1fb70edbdbbe65526b781e3a60f382d6cc

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checkpoint_2D.pt

pt · 9.33 GB · SHA-256 f7fb9f207d58…16fd · Hugging Face

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checkpoint_3D_checkpoint8.pt

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checkpoint_3D_LoRA2D.pt

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Source excerpts

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--- license: mit pipeline_tag: image-segmentation tags: - medical - foundation-model - sam3 - segmentation --- # Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation Medical SAM3 is a foundation model for universal prompt-driven medical image segmentation, obtained by fully fine-tuning SAM3 on large-scale, heterogeneous 2D and 3D medical imaging datasets with paired segmentation masks and text prompts. - **Paper:** [Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation](https://huggingface.co/papers/2601.10880) - **Project Page:** [https://chongcongjiang.github.io/MedicalSAM3/](https://chongcongjiang.github.io/MedicalSAM3/) - **Repository:** [https://github.com/AIM-Research-Lab/Medical-SAM3](https://github.com/AIM-Research-Lab/Medical-SAM3) ## Introduction Promptable segmentation foundation models such as SAM3 have demonstrated strong generalization capabilities through interactive and concept-based prompting. However, their direct applicability to medical image segmentation remains limited by severe domain shifts. By fine-tuning SAM3's model parameters on 33 datasets spanning 10 medical imaging modalities, Medical SAM3 acquires robust domain-specific representations while preserving prompt-driven flexibility. Experiments across organs, imaging modalities, and dimensionalities demonstrate consistent and significant performance gains. ## Citation ```bibtex @article{jiang2026medicalsam3, title={Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation}, author={Jiang, Chongcong and Ding, Tianxingjian and Song, Chuhan and Tu, Jiachen and Yan, Ziyang and Shao, Yihua and Wang, Zhenyi and Shang, Yuzhang and Han, Tianyu and Tian, Yu}, journal={arXiv preprint arXiv:2601.10880}, year={2026}, url={https://arxiv.org/abs/2601.10880} } ```

Source context: 5 downloads · 15 likes · Pipeline image-segmentation · Repo ChongCong/Medical-SAM3

Source context: 4 downloads · 12 likes · Pipeline image-segmentation · Repo ChongCong/Medical-SAM3