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README.md

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 pipeline_tag: image-segmentation
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-This is a segmentation model trained for pancretic lesion segmentation, presented in the paper [Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks](https://huggingface.co/papers/2510.14803). 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).
+This is a segmentation model trained for pancretic lesion segmentation, presented in the paper [Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks](https://huggingface.co/papers/2510.14803). It was trained with the Report Supervision ([R-Super](https://github.com/MrGiovanni/R-Super), MICCAI 2025, best paper award runner-up) training methodology, which **learns tumor segmentation directly from radiology reports** (through new loss functions).
 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).
 
 The AI model architecture is MedFormer, its training methology is Report Supervision (R-Super).