CT_CHAT
A major challenge in computational research in 3D medical imaging is the lack of comprehensive datasets. Addressing this issue, we present CT-RATE, the first 3D medical imaging dataset that pairs images with textual reports. CT-RATE consists of 25,692 non-contrast chest CT volumes, expanded to 50,188 through various reconstructions, from 21,304 unique patients, along with corresponding radiology text reports, multi-abnormality labels, and metadata. We divided the cohort into two groups: 20,000 patients were allocated to the training set and 1,304 to the validation set. Our folders are structured as split_patientID_scanID_reconstructionID. For instance, "valid_53_a_1" indicates that this is a CT volume from the validation set, scan "a" from patient 53, and reconstruction 1 of scan "a". This naming convention applies to all files.
Model Information
Model Access
Research and Citation
BibTeX
1. @article{hamamci2026generalist,
title={Generalist foundation models from a multimodal dataset for 3D computed tomography},
author={Hamamci, Ibrahim Ethem and Er, Sezgin and Wang, Chenyu and Almas, Furkan and Simsek, Ayse Gulnihan and Esirgun, Sevval Nil and Dogan, Irem and Durugol, Omer Faruk and Hou, Benjamin and Shit, Suprosanna and others},
journal={Nature Biomedical Engineering},
pages={1--19},
year={2026},
publisher={Nature Publishing Group UK London}
}
2. @inproceedings{hamamci2024generatect,
title={Generatect: Text-conditional generation of 3d chest ct volumes},
author={Hamamci, Ibrahim Ethem and Er, Sezgin and Sekuboyina, Anjany and Simsar, Enis and Tezcan, Alperen and Simsek, Ayse Gulnihan and Esirgun, Sevval Nil and Almas, Furkan and Do{\u{g}}an, Irem and Dasdelen, Muhammed Furkan and others},
booktitle={European Conference on Computer Vision},
pages={126--143},
year={2024},
organization={Springer}
}
3. @inproceedings{hamamci2024ct2rep,
title={Ct2rep: Automated radiology report generation for 3d medical imaging},
author={Hamamci, Ibrahim Ethem and Er, Sezgin and Menze, Bjoern},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={476--486},
year={2024},
organization={Springer}
}
4. @inproceedings{hamamci2025bettertokensbetter3d,
title={Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging},
author={Hamamci, Ibrahim Ethem and Er, Sezgin and Shit, Suprosanna and Reynaud, Hadrien and Yang, Dong and Guo, Pengfei and Edgar, Marc and Xu, Daguang and Kainz, Bernhard and Menze, Bjoern},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems}
}
5. @inproceedings{hamamci2025crg,
title={CRG Score: A Distribution-Aware Clinical Metric for Radiology Report Generation},
author={Hamamci, Ibrahim Ethem and Er, Sezgin and Shit, Suprosanna and Reynaud, Hadrien and Kainz, Bernhard and Menze, Bjoern},
booktitle={Medical Imaging with Deep Learning-Short Papers}
}