Git Product home page Git Product logo

challenge's Introduction

Federated Tumor Segmentation Challenge

The repo for the FeTS Challenge: The 1st Computational Competition on Federated Learning.

Website

https://www.synapse.org/#!Synapse:syn28546456

Challenge Tasks

Task 1

The first task of the challenge involves customizing core functions of a baseline federated learning system implementation. The goal is to improve over the baseline consensus models in terms of robustness in final model scores to data heterogeneity across the simulated collaborators of the federation. For more details, please see Task_1.

Task 2

This task utilizes federated testing across various sites of the FeTS initiative in order to evaluate model submissions across data from different medical institutions, MRI scanners, image acquisition parameters and populations. The goal of this task is to find algorithms (by whatever training technique you wish to apply) that score well across these data. For more details, please see Task_2.

Documentation and Q&A

Please visit the challenge website and forum.

Citation

Please cite this paper when using the data:

@misc{pati2021federated,
      title={The Federated Tumor Segmentation (FeTS) Challenge}, 
      author={Sarthak Pati and Ujjwal Baid and Maximilian Zenk and Brandon Edwards and Micah Sheller and G. Anthony Reina and Patrick Foley and Alexey Gruzdev and Jason Martin and Shadi Albarqouni and Yong Chen and Russell Taki Shinohara and Annika Reinke and David Zimmerer and John B. Freymann and Justin S. Kirby and Christos Davatzikos and Rivka R. Colen and Aikaterini Kotrotsou and Daniel Marcus and Mikhail Milchenko and Arash Nazer and Hassan Fathallah-Shaykh and Roland Wiest and Andras Jakab and Marc-Andre Weber and Abhishek Mahajan and Lena Maier-Hein and Jens Kleesiek and Bjoern Menze and Klaus Maier-Hein and Spyridon Bakas},
      year={2021},
      eprint={2105.05874},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}

challenge's People

Contributors

brandon-edwards avatar dependabot[bot] avatar geeks-sid avatar msheller avatar mzenk avatar psfoley avatar sarthakpati avatar sbakas avatar ujjwalbaid0408 avatar ywang037 avatar

Stargazers

 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.