Torch Radon Documentation

Torch Radon is a fast CUDA implementation of transforms needed for working with computed tomography data in Pytorch. It allows the training of end-to-end models that takes sinograms as inputs and produce images as output.

Main features:

• All operations work directly on Pytorch GPU tensors.

• Forward and back projections are differentiable and integrated with Pytorch .backward().

• Up to 50x faster than Astra Toolbox.

• Supports half precision and can used togheter with amp for faster training.

Projection types:

• Parallel Beam

• Fan Beam

Getting Started

• Google Colab
• Install Locally

Package reference

• Radon Projections
• Shearlet Transform
• Solvers

Indices and tables

• Index