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  This is a segmentation model trained for pancretic lesion segmentation. It was trained with the Report Supervision ([R-Super](https://github.com/MrGiovanni/R-Super), MICCAI 2025, best paper award finalist) training methodology, which **learns tumor segmentation directly from radiology reports** (through new loss functions).
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- This checkpoint was trained with **1,851 pancreatic lesion reports** from the Merlin dataset, plus **344 pancreatic lesion masks** from AbdomenAtlas 3.0 Beta.
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- Performance improvements are expected for models trained on the released version of AbdomenAtlas 3.0. For the ofifical release of AbdomenAtlas 3.0 (ICCV 2025), please check our GitHub: https://github.com/MrGiovanni/RadGPT.
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  The AI model architecture is MedFormer, its training methology is Report Supervision (R-Super).
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- Training and inference code: https://github.com/MrGiovanni/R-Super
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  <details>
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  <summary>Label order</summary>
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- ```python
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- ['adrenal_gland_left',
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- 'adrenal_gland_right',
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- 'aorta',
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- 'bladder',
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- 'celiac_trunk',
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- 'colon',
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- 'common_bile_duct',
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- 'duodenum',
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- 'esophagus',
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- 'femur_left',
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- 'femur_right',
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- 'gall_bladder',
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- 'hepatic_vessel',
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- 'intestine',
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- 'kidney_left',
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- 'kidney_lesion',
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- 'kidney_right',
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- 'liver',
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- 'liver_lesion',
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- 'liver_segment_1',
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- 'liver_segment_2',
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- 'liver_segment_3',
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- 'liver_segment_4',
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- 'liver_segment_5',
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- 'liver_segment_6',
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- 'liver_segment_7',
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- 'liver_segment_8',
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- 'lung_left',
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- 'lung_right',
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- 'pancreas',
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- 'pancreas_body',
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- 'pancreas_head',
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- 'pancreas_tail',
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- 'pancreatic_lesion',
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- 'portal_vein_and_splenic_vein',
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- 'postcava',
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- 'prostate',
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- 'rectum',
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- 'spleen',
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- 'stomach',
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- 'superior_mesenteric_artery',
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- 'veins']
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  ```
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  </details>
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@@ -84,11 +67,20 @@ If you use this data, please cite the 3 paper below:
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  year={2025}
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  }
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- @article{bassi2025radgpt,
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- title={Radgpt: Constructing 3d image-text tumor datasets},
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- author={Bassi, Pedro RAS and Yavuz, Mehmet Can and Wang, Kang and Chen, Xiaoxi and Li, Wenxuan and Decherchi, Sergio and Cavalli, Andrea and Yang, Yang and Yuille, Alan and Zhou, Zongwei},
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- journal={arXiv preprint arXiv:2501.04678},
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- year={2025}
 
 
 
 
 
 
 
 
 
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  }
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  ```
 
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  This is a segmentation model trained for pancretic lesion segmentation. It was trained with the Report Supervision ([R-Super](https://github.com/MrGiovanni/R-Super), MICCAI 2025, best paper award finalist) training methodology, which **learns tumor segmentation directly from radiology reports** (through new loss functions).
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+ This checkpoint was trained with public data: **1.8K pancreatic lesion reports** from the [Merlin](https://stanfordaimi.azurewebsites.net/datasets?domain=BODY) dataset, plus **0.9K pancreatic lesion masks** from [PanTS](https://github.com/MrGiovanni/PanTS).
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  The AI model architecture is MedFormer, its training methology is Report Supervision (R-Super).
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+ **Training and inference code: https://github.com/MrGiovanni/R-Super**
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  <details>
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  <summary>Label order</summary>
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+ ```yaml
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+ - adrenal_gland_left
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+ - adrenal_gland_right
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+ - aorta
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+ - bladder
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+ - colon
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+ - common_bile_duct
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+ - duodenum
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+ - femur_left
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+ - femur_right
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+ - gall_bladder
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+ - kidney_left
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+ - kidney_right
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+ - liver
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+ - lung_left
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+ - lung_right
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+ - pancreas
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+ - pancreas_body
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+ - pancreas_head
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+ - pancreas_tail
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+ - pancreatic_lesion
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+ - postcava
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+ - prostate
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+ - spleen
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+ - stomach
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+ - superior_mesenteric_artery
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+ - veins
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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  </details>
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  year={2025}
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  }
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+ @article{li2025pants,
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+ title={PanTS: The Pancreatic Tumor Segmentation Dataset},
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+ author={Li, Wenxuan and Zhou, Xinze and Chen, Qi and Lin, Tianyu and Bassi, Pedro RAS and Plotka, Szymon and Cwikla, Jaroslaw B and Chen, Xiaoxi and Ye, Chen and Zhu, Zheren and others},
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+ journal={arXiv preprint arXiv:2507.01291},
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+ year={2025},
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+ url={https://github.com/MrGiovanni/PanTS}
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+ }
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+
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+ @article{blankemeier2024merlin,
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+ title={Merlin: A vision language foundation model for 3d computed tomography},
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+ author={Blankemeier, Louis and Cohen, Joseph Paul and Kumar, Ashwin and Van Veen, Dave and Gardezi, Syed Jamal Safdar and Paschali, Magdalini and Chen, Zhihong and Delbrouck, Jean-Benoit and Reis, Eduardo and Truyts, Cesar and others},
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+ journal={Research Square},
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+ pages={rs--3},
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+ year={2024}
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  }
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  ```