https://github.com/cabouman/svmbir
Fast code for parallel or fan beam tomographic reconstruction
https://github.com/cabouman/svmbir
computed-tomography fan-beam parallel-beam plug-and-play python python3 reconstruction tomography
Last synced: 3 months ago
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Fast code for parallel or fan beam tomographic reconstruction
- Host: GitHub
- URL: https://github.com/cabouman/svmbir
- Owner: cabouman
- License: bsd-3-clause
- Created: 2020-07-08T14:33:13.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2024-05-23T16:10:15.000Z (almost 2 years ago)
- Last Synced: 2026-02-19T04:12:53.343Z (3 months ago)
- Topics: computed-tomography, fan-beam, parallel-beam, plug-and-play, python, python3, reconstruction, tomography
- Language: Python
- Homepage:
- Size: 5.21 MB
- Stars: 27
- Watchers: 14
- Forks: 8
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 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](https://github.com/HPImaging/sv-mbirct).*
Full documentation is available at [svmbir_docs](https://svmbir.readthedocs.io).
To cite this software package, please use the bibtext entry at [cite_svmbir](https://svmbir.readthedocs.io/en/latest/credits.html#references).
## 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](https://svmbir.readthedocs.io/en/latest/install.html#)
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.