.. grand-challenge.org documentation main file, created by sphinx-quickstart on Fri Jan 5 16:19:37 2018. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to grand-challenge.org's documentation! =============================================== In the era of Deep Learning, developing robust machine learning solutions to problems in biomedical imaging requires access to large amounts of annotated training data, objective comparisons of state of the art machine learning solutions, and clinical validation using real world data. `Grand Challenge`_ can assist Researchers, Data Scientists, and Clinicians in collaborating to develop these solutions by providing: Archives Manage medical imaging data. Reader Studies Train experts and have them annotate medical imaging data. Challenges Gather and objectively assess machine learning solutions. Algorithms Deploy machine learning solutions for clinical validation. Here, you find the documentation for the Django application that powers `Grand Challenge`_. You are able to use the instance there, add additional features by making a PR to our `GitHub repository`_, or spin up your own instance. .. toctree:: :maxdepth: 2 :caption: Contents: architecture development evaluation components workstations reader-studies design Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` .. _`Grand Challenge`: https://grand-challenge.org .. _`GitHub Repository`: https://github.com/comic/grand-challenge.org