Improve model card with pipeline tag and updated citations

README.md

@@ -1,4 +1,8 @@
-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).
+---
+pipeline_tag: image-segmentation
+---
+
+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 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).
@@ -42,6 +46,11 @@ The AI model architecture is MedFormer, its training methology is Report Supervi
 ---
 # Papers
 
+<b>Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks</b> <br/>
+[Pedro R. A. S. Bassi](https://scholar.google.com/citations?user=NftgL6gAAAAJ&hl=en), [Wenxuan Li](https://scholar.google.com/citations?hl=en&user=tpNZM2YAAAAJ), [Jieneng Chen](https://scholar.google.com/citations?user=yLYj88sAAAAJ&hl=zh-CN), Zheren Zhu, Tianyu Lin, [Sergio Decherchi](https://scholar.google.com/citations?user=T09qQ1IAAAAJ&hl=it), [Andrea Cavalli](https://scholar.google.com/citations?user=4xTOvaMAAAAJ&hl=en), [Kang Wang](https://radiology.ucsf.edu/people/kang-wang), [Yang Yang](https://scholar.google.com/citations?hl=en&user=6XsJUBIAAAAJ), [Alan Yuille](https://www.cs.jhu.edu/~ayuille/), [Zongwei Zhou](https://www.zongweiz.com/)* <br/>
+*Johns Hopkins University* <br/>
+<a href='https://huggingface.co/papers/2510.14803'><img src='https://img.shields.io/badge/Paper-PDF-purple'></a>
+
 <b>Learning Segmentation from Radiology Reports</b> <br/>
 [Pedro R. A. S. Bassi](https://scholar.google.com/citations?user=NftgL6gAAAAJ&hl=en), [Wenxuan Li](https://scholar.google.com/citations?hl=en&user=tpNZM2YAAAAJ), [Jieneng Chen](https://scholar.google.com/citations?user=yLYj88sAAAAJ&hl=zh-CN), Zheren Zhu, Tianyu Lin, [Sergio Decherchi](https://scholar.google.com/citations?user=T09qQ1IAAAAJ&hl=it), [Andrea Cavalli](https://scholar.google.com/citations?user=4xTOvaMAAAAJ&hl=en), [Kang Wang](https://radiology.ucsf.edu/people/kang-wang), [Yang Yang](https://scholar.google.com/citations?hl=en&user=6XsJUBIAAAAJ), [Alan Yuille](https://www.cs.jhu.edu/~ayuille/), [Zongwei Zhou](https://www.zongweiz.com/)* <br/>
 *Johns Hopkins University* <br/>
@@ -65,32 +74,34 @@ Louis Blankemeier, Joseph P. Cohen, Ashwin Kumar, ..., Akshay S. Chaudhari<br/>
 *Stanford* <br/>
 
 # Citations
-If you use this data, please cite the 3 paper below (model and datasets):
+If you use the code, data or methods in this repository, please cite:
 
 ```
-@article{bassi2025learning,
+@inproceedings{bassi2025learning,
   title={Learning Segmentation from Radiology Reports},
   author={Bassi, Pedro RAS and Li, Wenxuan and Chen, Jieneng and Zhu, Zheren and Lin, Tianyu and Decherchi, Sergio and Cavalli, Andrea and Wang, Kang and Yang, Yang and Yuille, Alan L and others},
-  journal={arXiv preprint arXiv:2507.05582},
-  year={2025}
-}
-
-@article{li2025pants,
-  title={PanTS: The Pancreatic Tumor Segmentation Dataset},
-  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},
-  journal={arXiv preprint arXiv:2507.01291},
+  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
+  pages={305--315},
   year={2025},
-  url={https://github.com/MrGiovanni/PanTS}
+  organization={Springer}
 }
 
-@article{blankemeier2024merlin,
-  title={Merlin: A vision language foundation model for 3d computed tomography},
-  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},
-  journal={Research Square},
-  pages={rs--3},
-  year={2024}
+@misc{bassi2025scaling,
+      title={Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks}, 
+      author={Pedro R. A. S. Bassi and Xinze Zhou and Wenxuan Li and Szymon Płotka and Jieneng Chen and Qi Chen and Zheren Zhu and Jakub Prządo and Ibrahim E. Hamacı and Sezgin Er and Yuhan Wang and Ashwin Kumar and Bjoern Menze and Jarosław B. Ćwikła and Yuyin Zhou and Akshay S. Chaudhari and Curtis P. Langlotz and Sergio Decherchi and Andrea Cavalli and Kang Wang and Yang Yang and Alan L. Yuille and Zongwei Zhou},
+      year={2025},
+      eprint={2510.14803},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2510.14803}, 
 }
 
+@article{bassi2025radgpt,
+  title={Radgpt: Constructing 3d image-text tumor datasets},
+  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},
+  journal={arXiv preprint arXiv:2501.04678},
+  year={2025}
+}
 ```
 
 ## Acknowledgement