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