From 2576b84c870c46e7c73415b93280c6dc79689718 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9=20Pedersen?= Date: Fri, 3 Nov 2023 13:43:17 +0100 Subject: [PATCH 1/3] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 844e5c9..48583f2 100644 --- a/README.md +++ b/README.md @@ -17,6 +17,7 @@ app_file: demo/app.py [![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) +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10069288.svg)](https://doi.org/10.5281/zenodo.10069288) **AeroPath** was developed by SINTEF Medical Image Analysis to accelerate medical AI research. @@ -26,7 +27,7 @@ app_file: demo/app.py 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) From 43eab4caa143d7398c4d1fde808ea4d52e17519a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9=20Pedersen?= Date: Fri, 3 Nov 2023 13:45:37 +0100 Subject: [PATCH 2/3] Added Zenodo bibtex to citation --- README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/README.md b/README.md index 48583f2..8f2be33 100644 --- a/README.md +++ b/README.md @@ -105,6 +105,22 @@ If you found the dataset and/or web application relevant in your research, pleas } ``` +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, From 9c1d43f1f19b1c91b3d8eeb78bd8c463a7d9650f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9=20Pedersen?= Date: Fri, 3 Nov 2023 13:48:58 +0100 Subject: [PATCH 3/3] Added arXiv preprint badge --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 8f2be33..e810986 100644 --- a/README.md +++ b/README.md @@ -18,6 +18,7 @@ app_file: demo/app.py [![CI/CD](https://github.com/raidionics/AeroPath/actions/workflows/deploy.yml/badge.svg)](https://github.com/raidionics/AeroPath/actions/workflows/deploy.yml) [![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.