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# Automatic lung tumor segmentation
This repository offers a proof of concept release of an automatic lung tumor segmentation method given a CT scan. Pre-trained weights are available for anyone to use. The repository structure is inspired by [Johannes Hofmanninger's lungmask repo](https://github.com/JoHof/lungmask), and part of the preprocessing pipeline is based on his lungmask release.
![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 [Hofmanninger's 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
```
## Limitations
This repository is a proof of concept. It is not intended to be used in clinical or commercial use. However, it might be interesting for research, play a role as a baseline, or even aid semi-supervised lung tumor segmentation.
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