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.
- 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
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
Training the GAN
python train_lung_gan.py
Extracting features
python extract_features.py
Training classifier
python train_classifier.py
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}
}