ResNet50 trained on PatchCamelyon (via TIA Toolbox)

This is a re-hosted version of the model available in the TIA Toolbox model zoo (licensed CC-BY-4.0).

Reusing the model

Coming soon...

Dataset

The PatchCamelyon dataset can be found on Zenodo https://zenodo.org/record/2546921 and on GitHub https://github.com/basveeling/pcam.

References

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}
@ARTICLE{Veeling2018-qh,
  title         = "Rotation Equivariant {CNNs} for Digital Pathology",
  author        = "Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and
                   Cohen, Taco and Welling, Max",
  month         =  jun,
  year          =  2018,
  archivePrefix = "arXiv",
  primaryClass  = "cs.CV",
  eprint        = "1806.03962"
}
@article{pocock2022tiatoolbox,
  title={TIAToolbox as an end-to-end library for advanced tissue image analytics},
  author={Pocock, Johnathan and Graham, Simon and Vu, Quoc Dang and Jahanifar, Mostafa and Deshpande, Srijay and Hadjigeorghiou, Giorgos and Shephard, Adam and Bashir, Raja Muhammad Saad and Bilal, Mohsin and Lu, Wenqi and others},
  journal={Communications medicine},
  volume={2},
  number={1},
  pages={120},
  year={2022},
  publisher={Nature Publishing Group UK London}
}