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--- |
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pipeline_tag: image-segmentation |
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tags: |
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- medical |
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- biology |
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- clinical |
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license: other |
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--- |
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# vesselFM |
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**TL;DR**: VesselFM is a foundation model for universal 3D blood vessel segmentation in arbitrary imaging domains. |
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For details, please refer to our preprint (https://arxiv.org/pdf/2411.17386) and our GitHub repo (https://github.com/bwittmann/vesselFM). |
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--- |
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### Checkpoints |
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We provide the following checkpoints: |
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- `vesselFM_base.pt`: VesselFM pre-trained on our three proposed data sources (D_real, D_drand, and D_flow). This checkpoint will be automatically downloaded in `vesselfm/seg/inference.py`. |
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### Citing vesselFM |
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If you find our work useful, please cite: |
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```bibtex |
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@InProceedings{Wittmann_2025_CVPR, |
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author = {Wittmann, Bastian and Wattenberg, Yannick and Amiranashvili, Tamaz and Shit, Suprosanna and Menze, Bjoern}, |
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title = {vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation}, |
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booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)}, |
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month = {June}, |
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year = {2025}, |
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pages = {20874-20884} |
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} |
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``` |
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