Detect common thoracic diseases from chest X-ray images. We are still working on it.

1. Setup pytorch(0.4.0) enviroment.
2. Download the dataset here.
3. Extract the images into directory dataset/images.
4. Put Data_Entry_2017.csv, BBox_List_2017.csv, test_list.txt, and train_val_list.txt into directory dataset.

To generate train, validation, and test data entry.

python label_gen.py

This will separate train_val_list.txt into train_list.txt and val_list.txt.
3 csv files train_label.csv, val_label.csv, and test_label.csv will be generated as data entry.

To train the model, You may modify the hyperparameters in the file and run

python train.py

To start tensorboard

tensorboard --logdir=./runs

See the following paper for more information about the dataset.
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, Ronald M. Summers. ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly- Supervised Classification and Localization of Common Thorax Diseases, IEEE CVPR, pp. 3462-3471,2017