MedicaVue's frontend

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

Website · Report Bug · Request Feature · Backend

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

• React
• Recoil
• Material-UI
• CornerstoneJS
• CornerstoneTools
• 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.

• Yarn : See instructions here.

Installation

1. Clone repo.

git clone https://github.com/YassineElbouchaibi/medica-vue-frontend.git

2. Install pacakages.

yarn

Usage

In the project directory, you can run:

yarn start

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

yarn build

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes.
Your app is ready to be deployed!

Deployment is done automatically by Netlify once code reaches master branch

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