MedicaVue's backend

Based on DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

Website · Report Bug · Request Feature · Frontend

Table of Contents

• About the Project
  • Built With
• Getting Started
  • Prerequisites
  • Installation
• Usage
• Roadmap
• Contributing
• License
• Contact
• Acknowledgements

About The Project

This was done in the context of a school project.

Backend Link: https://github.com/YassineElbouchaibi/medica-vue-backend

Frontend Link: https://github.com/YassineElbouchaibi/medica-vue-frontend

Built With

• Python
• Flask
• Tensorflow
• DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation
• And many other great packages! Visit the website to get a list of all of them.

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

• Docker : See instructions here.

Installation

1. Download app's static content (storage folder).

ggID='1ptCREx3GW6kHpRf7YxjjsvtF06lmDOMO'  
ggURL='https://drive.google.com/uc?export=download'  
filename="$(curl -sc /tmp/gcokie "${ggURL}&id=${ggID}" | grep -o '="uc-name.*</span>' | sed 's/.*">//;s/<.a> .*//')"  
getcode="$(awk '/_warning_/ {print $NF}' /tmp/gcokie)"  
curl -Lb /tmp/gcokie "${ggURL}&confirm=${getcode}&id=${ggID}" -o "${filename}"
unzip storage.zip

2. Pull container.

docker pull ghcr.io/yassineelbouchaibi/medica-vue.backend:latest

3. Start container (Replace with your values).

docker run -d -p <PORT_ON_YOUR_LOCAL_MACHINE>:80 \
  --name medica-vue.backend \
  -v "</absolute/path/to/storage>":/storage \
  -e STORAGE_ROOT=/storage \
  medica-vue.backend

Usage

docker start medica-vue.backend

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Yassine El Bouchaibi - Contact info coming soon...

Open an issue.

Acknowledgements

• DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation