DeepReg

DeepReg is a freely available, community-supported open-source toolkit for research and education in medical image registration using deep learning.

• TensorFlow2-based for efficient training and rapid deployment;
• Implementing major unsupervised and weakly-supervised algorithms, with their combinations and variants;
• Focusing on growing and diverse clinical applications, with all DeepReg Demos using open-accessible data;
• Simple built-in command line tools requiring minimal programming and scripting;
• Open, permissible and research-and-education-driven, under the Apache 2.0 license.

DeepReg^beta will be released in Autumn 2020 - however, many tutorials, demos and much of the core functionality are already accessible.

Getting Started

• Documentation, tutorials and a quick start guide
• DeepReg Demos
• Code: https://github.com/DeepRegNet/DeepReg
• Issue tracker: https://github.com/DeepRegNet/DeepReg/issues/new/choose
• Website: http://deepreg.net/

Contributing

Get involved, and help make DeepReg better!

For guidance on making a contribution to DeepReg, see the contribution guidelines.

If you identified a registration application with openly accessible data, please consider contributing a DeepReg Demo.

MICCAI 2020 Educational Challenge

The MICCAI Educational Challenge notebook can be accessed here or run it on Colab.