---
title: 'neukit: automatic brain extraction and preoperative tumor segmentation from MRI'
colorFrom: indigo
colorTo: indigo
sdk: docker
app_port: 7860
emoji: 🧠
pinned: false
license: mit
app_file: app.py
---

<div align="center">
<h1 align="center">neukit</h1>
<h3 align="center">Automatic brain extraction and preoperative tumor segmentation from MRI</h3>

[![license](https://img.shields.io/github/license/DAVFoundation/captain-n3m0.svg?style=flat-square)](https://github.com/DAVFoundation/captain-n3m0/blob/master/LICENSE)
[![CI/CD](https://github.com/andreped/neukit/actions/workflows/deploy.yml/badge.svg)](https://github.com/andreped/neukit/actions/workflows/deploy.yml)
<a target="_blank" href="https://huggingface.co./spaces/andreped/neukit"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-yellow.svg"></a>

**neukit** was developed by SINTEF Medical Image Analysis to accelerate medical AI research.

</div>

## Brief intro

This web application enables users to test [Raidionics](https://raidionics.github.io/), which is an open-source, free-to-use desktop application for pre- and postoperative central nervous system tumor segmentation and standardized reporting. The app only supports single volume input and only demonstrates the segmentation results of the Raidionics software, and thus is only meant for demonstration purposes.

For postoperative tumor segmentation, standardized reporting, and better functionality for performing analysis on full cohorts (batch mode), please, refer to the Raidionics software which is hosted [here](https://github.com/raidionics/Raidionics).

## Demo <a target="_blank" href="https://huggingface.co./spaces/andreped/neukit"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-yellow.svg"></a>

To access the live demo, click on the `Hugging Face` badge above. Below is a snapshot of the current state of the demo app.

<img width="1722" alt="Screenshot 2023-06-06 at 21 53 25" src="https://github.com/andreped/neukit/assets/29090665/e67f35c2-482b-409c-b1a9-bc987fbb5c6a">

## Development

### Docker

Alternatively, you can deploy the software locally. Note that this is only relevant for development purposes. Simply dockerize the app and run it:

```
docker build -t neukit .
docker run -it -p 7860:7860 neukit
```

Then open `http://127.0.0.1:7860` in your favourite internet browser to view the demo.

### Python

It is also possible to run the app locally without Docker. Just setup a virtual environment and run the app.
Note that the current working directory would need to be adjusted based on where `neukit` is located on disk.

```
git clone https://github.com/andreped/neukit.git
cd neukit/

virtualenv -ppython3 venv --clear
source venv/bin/activate
pip install -r requirements.txt

python app.py --cwd ./
```

## Troubleshooting

Note that due to `share=True` being enabled by default when launching the app,
internet access is required for the app to be launched. This can disabled by setting
the argument to `--share 0`.

## Citation

If you found the tool useful in your research, please, cite the corresponding software paper:

```
@misc{bouget2023raidionics,
    title={Raidionics: an open software for pre- and postoperative central nervous system tumor segmentation and standardized reporting}, 
    author={David Bouget and Demah Alsinan and Valeria Gaitan and Ragnhild Holden Helland and André Pedersen and Ole Solheim and Ingerid Reinertsen},
    year={2023},
    eprint={2305.14351},
    archivePrefix={arXiv},
    primaryClass={physics.med-ph}
}
```