DLTK documentation

DLTK is a neural networks toolkit written in python, on top of TensorFlow. It is developed to enable fast prototyping with a low entry threshold and ensure reproducibility in image analysis applications, with a particular focus on medical imaging. Its goal is to provide the community with state of the art methods and models and to accelerate research in this exciting field.

Getting started

For installation instructions and getting started please refer to the README.md. DLTK-specific tutorials and notebooks can be found in dltk/examples/tutorials and full examples with downloadable pre-trained models in dltk/examples/applications in the source.

Model Zoo

We also provide a model zoo in a separate repository for hosting (re-)implementations of existing or newly published work. For additional information and contact details, please refer to the individual README.md file in the code.


Twitter: @dltk_ Source on github.com Gitter chat: link


DLTK is currently maintained by Nick Pawlowski and Martin Rajchl with greatly appreciated contributions coming from individual researchers and engineers.

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