Physically corrected projectors for X-ray induced emission CT.
PyCorrectedEmissionCT is usually abbreviated to its python module name: corrct (either pronounced "corr-C-T" or "correct").
This package provides the following functionality:
- Support for attenuation correction of the forward-projection and back-projection.
- Various solvers (reconstruction algorithms):
- Simultaneous Iterative Reconstruction Technique (SIRT).
- Maximum Likelihood Estimation Maximisation (MLEM).
- Simultaneous Algebraic Reconstruction Technique (SART).
- Primal-dual optimization from Chambolle-Pock (Primal-Dual Hybrid Gradient - PDHG), with:
- Various data fitting terms, including Gaussian and Poisson noise modelling.
- Various optional regularization terms, including: TV-min, l1-min, laplacian, and wavelet l1-min.
- Multi-channel (collaborative) regularization terms, like: TNV (Total Nuclear Variation).
- Filtered Back-Projection (FBP), and its data-dependent filter learning variant (PyMR-FBP).
- Two projector backends, based on: astra-toolbox and scikit-image.
- Guided regularization parameter selection, through cross-validation and elbow method.
- Projection alignment routines.
It contains the code used for the following paper, which also provides a mathematical description of the attenuation correction concepts and algorithms used here:
- N. Viganò and V. A. Solé, "Physically corrected forward operators for
induced emission tomography: a simulation study," Meas. Sci. Technol., no.
Advanced X-Ray Tomography, pp. 1–26, Nov. 2017.
https://doi.org/10.1088/1361-6501/aa9d54
Other useful information:
- Free software: BSD 3-Clause license
- Documentation: https://cicwi.github.io/PyCorrectedEmissionCT/
It takes a few steps to setup PyCorrectedEmissionCT on your machine. We recommend installing Anaconda package manager for Python 3.
Simply install with:
conda install -c n-vigano corrct
If you want fast tomographic projectors using the astra-toolbox:
conda install -c astra-toolbox astra-toolbox
Simply install with:
pip install corrct
If you are on jupyter, and don't have the rights to install packages system-wide (e.g. on jupyter-slurm at ESRF), then you can install with:
! pip install --user corrct
To install PyCorrectedEmissionCT, simply clone this GitHub project. Go to the cloned directory and run PIP installer:
git clone https://github.com/cicwi/PyCorrectedEmissionCT.git corrct
cd corrct
pip install -e .
To learn more about the functionality of the package check out our examples folder.
- Nicola VIGANÒ - Main developer
- Jerome LESAINT - Contributor
- Patrick HARRISON - Contributor
See also the list of contributors who participated in this project.
Contributions are always welcome. Please submit pull requests against the main branch.
If you have any issues, questions, or remarks, then please open an issue on GitHub.
This project is licensed under the BSD license - see the LICENSE.md file for details.