Skip to content

askorikov/flexTOMO

 
 

Repository files navigation

flexTOMO

This project is a part of the larger X-ray tomographic reconstruction toolbox comprised of [flexDATA], [flexTOMO] and [flexCALC]. flexTOMO provides a wrapper around a GPU-based tomographic reconstruction toolbox ASTRA. The main purpose of this project is to provide an easy way to use cone-beam forward- and back-projectors. Another purpose is to collect various algebraic reconstruction algorithms, providing support for large disk-mapped arrrays (memmaps) and subsets that allow to both accelerate convergence and to save RAM.

Getting Started

Before installing flexTOMO, please download and install flexDATA. Once installation of flexDATA is complete, one can install flexTOMO from the source code or using Anaconda.

Installing with conda

Simply install with:

conda create -n <your-environment> python=3.7
conda install -c cicwi -c astra-toolbox/label/dev -c conda-forge -c owlas flextomo

Installing from source

To install flexTOMO you will need the latest version of the ASTRA toobox (preferably development version). We also recommend to install Xraylib module using Anaconda from the Conda-Forge channel:

conda install -c astra-toolbox/label/dev astra-toolbox
conda install -c conda-forge xraylib 

To install flexTOMO, simply clone this GitHub project. Go to the cloned directory and run PIP installer:

git clone https://github.com/cicwi/flextomo.git
cd flexdata
pip install -e .

Running the examples

To learn about the functionality of the package check out our examples folder. Examples are separated into blocks that are best to run in Spyder environment step-by-step.

Modules

flexTOMO is comprised of two modules:

  • phantom: a very simple modelue with a few phantom object generators
  • project: main module that contains forward- and back-projectors, and algebraic reconstruction algorithms

Typical code:

# Import:
import numpy

from flextomo import project
from flextomo import phantom

# Initialize projection images:    
proj = numpy.zeros([512, 361, 512], dtype = 'float32')

# Define a simple projection geometry:
geom = geometry.circular(src2obj = 100, det2obj = 100, det_pixel = 0.01, ang_range = [0, 360])

# Create phantom and project into proj:
vol = phantom.abstract_nudes([512, 512, 512], geom, complexity = 10)

# Forward project:
project.forwardproject(proj, vol, geometry)

Authors and contributors

  • Alexander Kostenko - Initial work

See also the list of contributors who participated in this project.

How to contribute

Contributions are always welcome. Please submit pull requests against the develop branch.

If you have any issues, questions, or remarks, then please open an issue on GitHub.

License

This project is licensed under the GNU GENERAL PUBLIC License - see the LICENSE.md file for details

Acknowledgments

  • To Willem Jan Palenstijn for endles advices regarding the use of ASTRA toolbox.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 77.7%
  • Makefile 12.7%
  • Batchfile 9.5%
  • Shell 0.1%