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.

Installation

Stable latest release:

pip install https://github.com/VemundFredriksen/LungTumorMask/releases/download/v1.1.0/lungtumormask-1.1.0-py2.py3-none-any.whl

Or from source:

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}
}