Path2AI/STARC-9

Paper link is given here: Openreview or Arxiv .

To learn more about dataset generation using DeepCluster++, see the detailed documentation here.

For training and validation of baseline and foundation classifier models using the generated dataset, visit here.

Both the collected dataset and the trained model have been made publicly available for research use. Visit here .

If you find our work useful in your research or use parts of this code or dataset, please consider citing our research work.

APA 6

Subramanian, B., Jeyaraj, R., Peterson, M. N., Guo, T., Shah, N., Langlotz, C., Ng, A. Y., & Shen, J. (2025). STARC-9: A large-scale dataset for multi-class tissue classification for CRC histopathology. In The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track. https://openreview.net/forum?id=rGWjTlK6Ev

BibTex

@inproceedings{
subramanian2025starc,
title={{STARC}-9: A Large-scale Dataset for Multi-Class Tissue Classification for {CRC} Histopathology},
author={Barathi Subramanian and Rathinaraja Jeyaraj and Mitchell Nevin Peterson and Terry Guo and Nigam Shah and Curtis Langlotz and Andrew Y. Ng and Jeanne Shen},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2025},
url={https://openreview.net/forum?id=rGWjTlK6Ev}
}


LICENSE
---

license: cc-by-4.0
task_categories:
- image-classification
language:
- en
tags:
- medical
- histopathology
- colorectal-cancer
pretty_name: STARC-9
size_categories:
- 1B<n<10B
version: 0.1.0-draft 

---

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