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AbdomenAtlas 3.0 is the first public dataset with high quality abdominal CTs and paired radiology reports. The database includes more than 9,000 CT scans with radiology reports and per-voxel annotations of liver, kidney and pancreatic tumors.
Moreover, we present RadGPT, a segmentation-based report generation model which significantly surpasses the current state of the art in report generation for abdominal CTs.
Our “superhuman” reports are more accurate, detailed, standardized, and generated faster than traditional human-made reports. Email [email protected] to get early access to this dataset.
RadGPT: Constructing 3D Image-Text Tumor Datasets
Pedro R. A. S. Bassi, Mehmet Yavuz, Kang Wang, Xiaoxi Chen, Wenxuan Li, Sergio Decherchi, Andrea Cavalli, Yang Yang, Alan Yuille, Zongwei Zhou*
Johns Hopkins University
@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},
url={https://github.com/MrGiovanni/RadGPT}
}
This work was supported by the Lustgarten Foundation for Pancreatic Cancer Research and the McGovern Foundation. Paper content is covered by patents pending.