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SPIDER-thorax-model

Image Classification
Transformers
Safetensors
SPIDERPatchClassifier
feature-extraction
custom_code
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metadata
library_name: transformers
license: cc-by-nc-4.0
datasets:
  - histai/SPIDER-thorax
base_model:
  - histai/hibou-L
pipeline_tag: image-classification

SPIDER-Thorax Model

Model Description

SPIDER-thorax model is a deep learning model trained for patch-level pathology classification, specifically for thorax. 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 [email protected].

Model Sources

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-thorax-model", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("histai/SPIDER-thorax-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-thorax dataset, a subset of the SPIDER dataset. The dataset includes:

Class Central Patches
Alveoli 6652
Bronchial cartilage 5685
Bronchial glands 4412
Chronic inflammation + fibrosis 6070
Detritus 5146
Fibrosis 6494
Hemorrhage 5247
Lymph node 6088
Pigment 5177
Pleura 4560
Tumor non-small cell 6445
Tumor small cell 5061
Tumor soft 5894
Vessel 5376

Total Counts:

  • 78,307 central patches
  • 599,459 total patches (including context patches)
  • 411 total slides used for annotation

Results

Organ Accuracy Precision F1 Score
Thorax 0.962 0.958 0.960

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