Automatic lung tumor segmentation in CT

This is the official repository for the paper "Teacher-student approach for lung tumor segmentation from mixed-supervised datasets", published in PLOS ONE.

A pretrained model is made available in a command line tool and can be used as you please. However, the current model is not intended for clinical use. The model is the result of a proof-of-concept study. An improved model will be made available in the future, when more training data is made available.

Dependencies

In addition to the python packages specified in requirements.txt, PyTorch and lungmask must be installed.

Installation

pip install git+https://github.com/VemundFredriksen/LungTumorMask

Usage

After install, the software can be used as a command line tool. Simply specify the input and output filenames to run:

# Format
lungtumormask input_file output_file

# Example
lungtumormask patient_01.nii.gz mask_01.nii.gz

Acknowledgements

If you found this repository useful in your study, please, cite the following paper:

@article{fredriksen2021teacherstudent,
title = {Teacher-student approach for lung tumor segmentation from mixed-supervised datasets},
author = {Fredriksen, Vemund AND Sevle, Svein Ole M. AND Pedersen, André AND Langø, Thomas AND Kiss, Gabriel AND Lindseth, Frank},
journal = {PLOS ONE},
publisher = {Public Library of Science},
year = {2022},
month = {04},
doi = {10.1371/journal.pone.0266147},
volume = {17},
url = {https://doi.org/10.1371/journal.pone.0266147},
pages = {1-14},
number = {4}}