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# Automatic lung tumor segmentation in CT | |
This is the official repository for the paper [_"Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation"_](https://arxiv.org/abs/2112.11541), 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. | |
![sample of masked output](https://github.com/VemundFredriksen/LungTumorMask/releases/download/0.0.1/sample_images.png "Sample output of two different tumors") | |
![sample of 3d render](https://github.com/VemundFredriksen/LungTumorMask/releases/download/0.0.1/sample_renders.png "3D render of two masked outputs") | |
## Dependencies | |
In addition to the python packages specified in requirements.txt, [PyTorch](https://pytorch.org/get-started/locally/) and [lungmask](https://github.com/JoHof/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}} | |
``` | |