Lung-GANs

This is the code for Lung-GANs: Unsupervised Representation Learning for Lung Disease Classification using Chest CT and X-ray Images. Lung-GANs is a deep unsupervised framework to classify lung diseases from chest CT and X-ray images.

Dataset

• Tuberculosis vs. Healthy: https://mmcheng.net/tb/
• Healthy vs. Sick : https://mmcheng.net/tb/
• Pneumonia vs. Normal : https://data.mendeley.com/datasets/rscbjbr9sj/2
• COVID-19 vs. Pneumonia : https://www.kaggle.com/tawsifurrahman/covid19-radiography-database
• COVID-19 vs. Non-COVID CT & X-ray : https://data.mendeley.com/datasets/8h65ywd2jr/3

Dependencies

NVIDIA GPU + CUDA CuDNN (CPU mode and CUDA without CuDNN mode are also available but is significantly slower)

• tensorflow - 1.15.0
• tensorlayer - 1.6.0
• sklearn - 0.20.4
• numpy - 1.16.1

Usage

Training the GAN

python train_lung_gan.py

Extracting features

python extract_features.py

Training classifier

python train_classifier.py

Citation

If this code is useful for your research, do cite:

@article{yadav2021lung,
  title={Lung-GANs: Unsupervised Representation Learning for Lung Disease Classification Using Chest CT and X-Ray Images},
  author={Yadav, Pooja and Menon, Neeraj and Ravi, Vinayakumar and Vishvanathan, Sowmya},
  journal={IEEE Transactions on Engineering Management},
  year={2021},
  publisher={IEEE}
}