MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images

Qinyue Tong¹ · Ziqian Lu² · Jun Liu¹
Rui Zuo¹ · Zhe-ming Lu^1
1Zhejiang University, ²Zhejiang Sci-Tech University
🧑‍💼 Project Leader: Prof. Zhe-ming Lu

📣 News

• 2025.11.20: We’ve uploaded our paper MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images to arXiv and set up this repository! Welcome to watch 👀 this repository for the latest updates.

📝 ToDo List

• Release training codes.
• Release MR-MedSeg benchmark.
• Release evaluating codes.
• Release demo codes and MediRound pre-trained weights.

📷 Video Demo Presentation

You can watch the MediRound demo video to better understand its mechanism and workflow. You can either click the play button below or use the link MediRound Demo Presentation.

👏 Acknowledgements

This project is developed on the codebase of SegLLM and data from SA-Med2D-20M Dataset. We appreciate their valuable contributions!

🤟 Citation

If you find our paper is helpful for your research, please consider citing:

@article{tong2025mediround,
  title={MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images},
  author={Tong, Qinyue and Lu, Ziqian and Liu, Jun and Zuo, Rui and Lu, Zheming},
  journal={arXiv preprint arXiv:2511.12110},
  year={2025}
}