Automatic lung tumor segmentation in CT

This is the official repository for the paper "Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation", submitted to PLOS ONE.

A pretrained model is made available and can be used as you please. However, the current model is not intended for clinical use. The model is a result of a proof-of-concept study, and an improved model will be made available in the near 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

When the package is installed through pip, simply specify the input and output filenames.

# 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:

@misc{fredriksen2021teacherstudent,
title={Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation}, 
author={Vemund Fredriksen and Svein Ole M. Svele and André Pedersen and Thomas Langø and Gabriel Kiss and Frank Lindseth},
year={2021},
eprint={2112.11541},
archivePrefix={arXiv},
primaryClass={eess.IV}}