Usage Examples¶

Example Dependencies¶

Some examples use additional dependencies, which are listed in examples_requirements.txt. The additional requirements should be installed via pip, with the exception of astra-toolbox, which should be installed via conda:

conda install astra-toolbox
pip install -r examples/examples_requirements.txt  # Installs other example requirements

The dependencies can also be installed individually as required.

Note that astra-toolbox should be installed on a host with one or more CUDA GPUs to ensure that the version with GPU support is installed.

Run Time¶

Most of these examples have been constructed with sufficiently small test problems to allow them to run to completion within 5 minutes or less on a reasonable workstation. Note, however, that it was not feasible to construct meaningful examples of the training of some of the deep learning algorithms that complete within a relatively short time; the examples “CT Training and Reconstructions with MoDL” and “CT Training and Reconstructions with ODP” in particular are much slower, and can require multiple hours to run on a workstation with multiple GPUs.

Organized by Application¶

Computed Tomography¶

Deconvolution¶

Sparse Coding¶

Miscellaneous¶

Organized by Regularization¶

Plug and Play Priors¶

Total Variation¶

Sparsity¶

Machine Learning¶

Organized by Optimization Algorithm¶

ADMM¶

Linearized ADMM¶

Proximal ADMM¶

Non-linear Proximal ADMM¶

Complex Total Variation Denoising with NLPADMM Solver

PDHG¶

PGM¶

PCG¶

CT Reconstruction with CG and PCG