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 -c astra-toolbox 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#

PDHG#

PGM#

PCG#