
A lymphocyte classification model. This model is an InceptionV4 (without batch normalization)
and was trained on 23 types of cancers from TCGA.

Please refer to the [original GitHub Repo](https://github.com/ShahiraAbousamra/til_classification) 
and the [associated paper](https://doi.org/10.3389/fonc.2021.806603). If you find this model useful,
please consider citing relevant paper:

```bibtex
@article{abousamra2022deep,
  title={Deep learning-based mapping of tumor infiltrating lymphocytes in whole slide images of 23 types of cancer},
  author={Abousamra, Shahira and Gupta, Rajarsi and Hou, Le and Batiste, Rebecca and Zhao, Tianhao and Shankar, Anand and Rao, Arvind and Chen, Chao and Samaras, Dimitris and Kurc, Tahsin and others},
  journal={Frontiers in oncology},
  volume={11},
  pages={5971},
  year={2022},
  publisher={Frontiers}
}
```

The model was converted from its original TF Slim implementation to PyTorch using the script
`convert_tf_to_pytorch_til_inceptionv4.py` (in this repository).
{"license": "cc-by-4.0", "library_name": "pytorch"}
pytorch license:cc-by-4.0 region:us
TAGS
#pytorch #license-cc-by-4.0 #region-us 


A lymphocyte classification model. This model is an InceptionV4 (without batch normalization)
and was trained on 23 types of cancers from TCGA.

Please refer to the original GitHub Repo 
and the associated paper. If you find this model useful,
please consider citing relevant paper:



The model was converted from its original TF Slim implementation to PyTorch using the script
'convert_tf_to_pytorch_til_inceptionv4.py' (in this repository).
TAGS
#pytorch #license-cc-by-4.0 #region-us 
