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[UNOFFICIAL]

This is a unofficial, rehosted repository for CTransPath. The original and official repository is https://github.com/Xiyue-Wang/TransPath and the paper is https://www.sciencedirect.com/science/article/abs/pii/S1361841522002043

CTransPath is released under the GPLv3 License and is available for non-commercial academic purposes.

This work is not affiliated with the authors of CTransPath and is intended to help others reuse the model.

Please use the following transform with this model.

from torchvision import transforms

mean = (0.485, 0.456, 0.406)
std = (0.229, 0.224, 0.225)
trnsfrms_val = transforms.Compose(
    [
        transforms.Resize(224),
        transforms.ToTensor(),
        transforms.Normalize(mean = mean, std = std)
    ]
)

If you find this useful, cite the papers of the CTransPath authors. Please also check the authors' GitHub repository for any other papers to cite.

@{wang2022,
  title={Transformer-based Unsupervised Contrastive Learning for Histopathological Image Classification},
  author={Wang, Xiyue and Yang, Sen and Zhang, Jun and Wang, Minghui and Zhang, Jing  and Yang, Wei and Huang, Junzhou  and Han, Xiao},
  journal={Medical Image Analysis},
  year={2022},
  publisher={Elsevier}
}
@inproceedings{wang2021transpath,
  title={TransPath: Transformer-Based Self-supervised Learning for Histopathological Image Classification},
  author={Wang, Xiyue and Yang, Sen and Zhang, Jun and Wang, Minghui and Zhang, Jing and Huang, Junzhou and Yang, Wei and Han, Xiao},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={186--195},
  year={2021},
  organization={Springer}
}
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27.8M params
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I64
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F32
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