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Merge pull request #48 from raidionics/zenodo
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andreped authored Nov 3, 2023
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[![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/🤗%20Hugging%20Face-Spaces-yellow.svg"></a>
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10069288.svg)](https://doi.org/10.5281/zenodo.10069288)
[![paper](https://img.shields.io/badge/arXiv-preprint-D12424)]([arXiv](https://arxiv.org/abs/2311.01138))

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

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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 [here](https://zenodo.org/records/10069289).
The dataset is made openly available at Zenodo [here](https://zenodo.org/records/10069289).

## [Dataset structure](https://github.com/raidionics/AeroPath#data-structure)

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}
```

The dataset is hosted at Zenodo, so you should also cite the following:
```
@dataset{hofstad_2023_10069289,
author = {Hofstad, Erlend and
Bouget, David and
Pedersen, André},
title = {{AeroPath: An airway segmentation benchmark dataset
with challenging pathology}},
month = nov,
year = 2023,
publisher = {Zenodo},
doi = {10.5281/zenodo.10069289},
url = {https://doi.org/10.5281/zenodo.10069289}
}
```

The web application is using the [Raidionics]() backend, thus, also consider citing:
```
@article{bouget2023raidionics,
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