Spaces:
Running
Running
File size: 5,537 Bytes
241ef3e 21400f7 241ef3e 1b4af4d 241ef3e c468f0b 3b9d4b9 241ef3e 61aa9bc 241ef3e 3209aa9 241ef3e 2c7d43a 61aa9bc 241ef3e af8f367 241ef3e 7c28338 61aa9bc 241ef3e 61aa9bc 241ef3e 61aa9bc 241ef3e 6b70d16 241ef3e 6b70d16 241ef3e 6b70d16 241ef3e 1b4af4d 241ef3e 61aa9bc 241ef3e 3209aa9 241ef3e 3209aa9 241ef3e 49e2598 c468f0b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 |
---
title: 'AeroPath: automatic airway segmentation using deep learning'
colorFrom: indigo
colorTo: indigo
sdk: docker
app_port: 7860
emoji: π«
pinned: false
license: mit
app_file: demo/app.py
---
<div align="center">
<h1 align="center">π« AeroPath π€</h1>
<h3 align="center">An airway segmentation benchmark dataset with challenging pathology</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/raidionics/AeroPath/actions/workflows/deploy.yml/badge.svg)](https://github.com/raidionics/AeroPath/actions/workflows/deploy.yml)
<a target="_blank" href="https://huggingface.co/spaces/andreped/AeroPath"><img src="https://img.shields.io/badge/π€%20Hugging%20Face-Spaces-yellow.svg"></a>
**AeroPath** was developed by SINTEF Medical Image Analysis to accelerate medical AI research.
</div>
## [Brief intro](https://github.com/raidionics/AeroPath#brief-intro)
This repository contains the AeroPath dataset described in ["_AeroPath: An airway segmentation benchmark dataset with challenging pathology_"](https://arxiv.org/abs/2311.01138). A web application was also developed in the study, to enable users to easily test our deep learning model on their own data. The application was developed using [Gradio](https://www.gradio.app) for the frontend and the segmentation is performed using the [Raidionics](https://raidionics.github.io/) backend.
The dataset can be accessed from [Releases](https://github.com/raidionics/AeroPath/releases).
## [Dataset structure](https://github.com/raidionics/AeroPath#data-structure)
The dataset contains 27 CTs with corresponding airways and lung annotations. The folder structure is described below:
```
βββ AeroPath.zip
βββ README.md
βββ AeroPath/
βββ pat1/
β βββ pat1_ct.nii.gz
β βββ pat1_airways.nii.gz
β βββ pat1_lungs.nii.gz
βββ [...]
βββ pat27/
βββ pat27_ct.nii.gz
βββ pat27_airways.nii.gz
βββ pat27_lungs.nii.gz
```
## [Demo](https://github.com/raidionics/AeroPath#demo) <a target="_blank" href="https://huggingface.co/spaces/andreped/AeroPath"><img src="https://img.shields.io/badge/π€%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="1400" alt="Screenshot 2023-10-31 at 01 34 47" src="https://github.com/raidionics/AeroPath/assets/29090665/bd2db9ff-b188-4f90-aa96-4723b8e7597c">
## [Continuous integration](https://github.com/raidionics/AeroPath#continuous-integration)
| Build Type | Status |
| - | - |
| **HF Deploy** | [![Deploy](https://github.com/raidionics/AeroPath/workflows/Deploy/badge.svg)](https://github.com/raidionics/AeroPath/actions) |
| **File size check** | [![Filesize](https://github.com/raidionics/AeroPath/workflows/Check%20file%20size/badge.svg)](https://github.com/raidionics/AeroPath/actions) |
| **Formatting check** | [![Filesize](https://github.com/raidionics/AeroPath/workflows/Linting/badge.svg)](https://github.com/raidionics/AeroPath/actions) |
## [Development](https://github.com/raidionics/AeroPath#development)
### [Docker](https://github.com/raidionics/AeroPath#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 AeroPath .
docker run -it -p 7860:7860 AeroPath
```
Then open `http://127.0.0.1:7860` in your favourite internet browser to view the demo.
### [Python](https://github.com/raidionics/AeroPath#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 `AeroPath` is located on disk.
```
git clone https://github.com/raidionics/AeroPath.git
cd AeroPath/
virtualenv -python3 venv --clear
source venv/bin/activate
pip install -r ./demo/requirements.txt
python demo/app.py --cwd ./
```
## [Citation](https://github.com/raidionics/AeroPath#citation)
If you found the dataset and/or web application relevant in your research, please cite the following reference:
```
@misc{stΓΈverud2023aeropath,
title={{AeroPath: An airway segmentation benchmark dataset with challenging pathology}},
author={Karen-Helene StΓΈverud and David Bouget and Andre Pedersen and HΓ₯kon Olav Leira and Thomas LangΓΈ and Erlend Fagertun Hofstad},
year={2023},
eprint={2311.01138},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
The web application is using the [Raidionics]() backend, thus, also consider citing:
```
@article{bouget2023raidionics,
title = {Raidionics: an open software for pre-and postoperative central nervous system tumor segmentation and standardized reporting},
author = {Bouget, David and Alsinan, Demah and Gaitan, Valeria and Holden Helland, Ragnhild and Pedersen, AndrΓ© and Solheim, Ole and Reinertsen, Ingerid},
year = {2023},
month = {09},
pages = {},
volume = {13},
journal = {Scientific Reports},
doi = {10.1038/s41598-023-42048-7},
}
```
## [License](https://github.com/raidionics/AeroPath#license)
The code in this repository is released under [MIT license](https://github.com/raidionics/AeroPath/blob/main/LICENSE.md).
|