svmbir 0.4.0

Python code for fast parallel-beam MBIR (Model Based Iterative Reconstruction)

svmbir

Python code for fast MBIR (Model Based Iterative Reconstruction)
This is a python wrapper for High Performance Imaging's supervoxel C code, HPImaging/sv-mbirct.

Full documentation is available at svmbir_docs.

To cite this software package, please use the bibtext entry at cite_svmbir.

Installing svmbir

Currently supporting Python 3.9-3.12, on MacOS and Linux (Windows possible but not actively maintained).

svmbir packages are available from conda-forge and PyPI, or can be built and installed from source.

• (recommended) Create a clean virtural environment, such as

conda create -n svmbir python=3.10
conda activate svmbir

• To install from conda-forge,

conda install -c conda-forge svmbir

• To install from PyPI,

pip install svmbir

• Installing from source (requires GNU/gcc compiler, OMP libraries),

# In top repository folder,
CC=gcc pip install .        # also supports Intel "icc"

See here for more details.

Running the demos

1. Download demo.zip at https://github.com/cabouman/svmbir/blob/master/demo.zip.
2. Uncompress the zip file and change into demo folder.
3. In your terminal window, install required dependencies of demo.

pip install -r requirements_demo.txt

4. In your terminal window, use python to run each demo.