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MCP-MedSAM

Pytorch Implementation of the paper "MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day". This paper introduces a new variant of MedSAM, integrating a lightweight pre-trained tiny ViT, two novel prompts (modality prompt and content prompt), and a modality-based data sampling strategy. These enhancements enable the model to achieve strong performance without long training time and large GPU resource consumption. The code will come soon.

Citation

@misc{lyu2024mcpmedsampowerfullightweightmedical,
      title={MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day}, 
      author={Donghang Lyu and Ruochen Gao and Marius Staring},
      year={2024},
      eprint={2412.05888},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.05888}, 
}