thomascong121/CAGAN_Stain_Norm

Source code of the paper "Colour adaptive generative networks for stain normalisation of histopathology images" presented in Medical Image Analysis, 2022

CAGAN_Stain_Norm

Configs

All configs are located configs folder

Training

For training the modeld section, simply run python3 main.py dataset=cam16. You may specifiy the dataset using dataset=[tcga|breakhis|cam16|cam17].

Testing

For testing the model, simply run python3 main.py dataset=cam16 run=test. You may specifiy the dataset using dataset=[tcga|breakhis|cam16|cam17]. For classifier training, simply run python3 classifier.py dataset=cam17 model=classifier run.opt_run.n_epoch=40. You may specifiy the dataset using dataset=[tcga|breakhis|cam17].

Trained Packages

We provide several pretrained trained models. We also provide our train-test splits.

method	Dataset	url
CAGAN	TCGA-IDH	model
CAGAN	BreakHis	model
CAGAN	CAMELYON16	model

Citing Paper

Please cite following paper if these codes help your research

@article{cong2022colour, title={Colour adaptive generative networks for stain normalisation of histopathology images}, author={Cong, Cong and Liu, Sidong and Di Ieva, Antonio and Pagnucco, Maurice and Berkovsky, Shlomo and Song, Yang}, journal={Medical Image Analysis}, pages={102580}, year={2022}, publisher={Elsevier} }