Repository features UNet inspired architecture used for segmenting lungs on chest 3D tomography images.
Run inference.py
to see the application of the model on Demo files.
Implemented in Keras(2.0.4) with TensorFlow(1.1.0) as backend.
To use this implementation one needs to load and preprocess data (see load_data.py
), train new model if needed (train_model.py
) and use the model for generating lung masks (inference.py
).
trained_model.hdf5
and trained_model_wc.hdf5
contain models trained on private data set without and with coordinates channels.