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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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datasets: |
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- histai/SPIDER-colorectal |
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base_model: |
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- histai/hibou-L |
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pipeline_tag: image-classification |
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--- |
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# SPIDER-Colorectal Model |
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### Model Description |
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SPIDER-colorectal model is a deep learning model trained for patch-level pathology classification, specifically for colorectal. It is part of the SPIDER dataset initiative, which provides a large, high-quality, multi-organ pathology dataset with expert-annotated labels. |
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If you would like to support, sponsor, or obtain a commercial license for the SPIDER data and models, please contact us at [email protected]. |
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### Model Sources |
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- **Repository:** [https://github.com/HistAI/SPIDER](https://github.com/HistAI/SPIDER) |
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- **Paper:** [SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models](https://arxiv.org/abs/2503.02876) |
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## How to Get Started with the Model |
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Model works with **1120×1120** patches. |
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Use the following code snippet to load and use the model: |
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```python |
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from transformers import AutoModel, AutoProcessor |
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from PIL import Image |
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model = AutoModel.from_pretrained("histai/SPIDER-colorectal-model", trust_remote_code=True) |
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processor = AutoProcessor.from_pretrained("histai/SPIDER-colorectal-model", trust_remote_code=True) |
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image = Image.open("path_to_image.png") |
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inputs = processor(images=image, return_tensors="pt") |
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outputs = model(**inputs) |
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print(outputs.predicted_class_names) |
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``` |
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### Training Data |
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The model is trained on the [SPIDER-colorectal](https://huggingface.co/datasets/histai/SPIDER-colorectal) dataset, a subset of the SPIDER dataset. The dataset includes: |
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| Class | Central Patches | |
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|--------------------------------|------------| |
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| Adenocarcinoma high grade | 6299 | |
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| Adenocarcinoma low grade | 6066 | |
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| Adenoma high grade | 5493 | |
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| Adenoma low grade | 5693 | |
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| Fat | 6081 | |
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| Hyperplastic polyp | 5893 | |
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| Inflammation | 5523 | |
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| Mucus | 5711 | |
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| Muscle | 5866 | |
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| Necrosis | 5481 | |
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| Sessile serrated lesion | 4993 | |
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| Stroma healthy | 8001 | |
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| Vessels | 6082 | |
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**Total Counts:** |
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- **77,182** central patches |
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- **1,039,150** total patches (including context patches) |
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- **1,719** total slides used for annotation |
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### Results |
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| Organ | Accuracy | Precision | F1 Score | |
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|---------|----------|------------|----------| |
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| Colorectal | 0.914 | 0.917 | 0.915 | |
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## License |
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The model is licensed under **CC BY-NC 4.0** and is for **research use only**. |
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## Citation |
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If you use this model, please cite the following: |
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```bibtex |
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@misc{nechaev2025spidercomprehensivemultiorgansupervised, |
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title={SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models}, |
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author={Dmitry Nechaev and Alexey Pchelnikov and Ekaterina Ivanova}, |
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year={2025}, |
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eprint={2503.02876}, |
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archivePrefix={arXiv}, |
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primaryClass={eess.IV}, |
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url={https://arxiv.org/abs/2503.02876}, |
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} |
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``` |
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## More Information |
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To explore other models and the SPIDER dataset you can visit the [Hugging Face HistAI page](https://huggingface.co/histai) or [GitHub](https://github.com/HistAI/SPIDER) of the project. |
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## Contacts |
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- **Authors:** Dmitry Nechaev, Alexey Pchelnikov, Ekaterina Ivanova |
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- **Email:** [email protected], [email protected], [email protected] |
