Introduction¶
There are several methods to compute the inverse Radon transform.
The module radontea
implements some of them. I focused on
code readability and thorough comments. The result is a collection of
algorithms that are suitable for teaching the basics of
computerized tomography.
Recommended literature¶
- Aninash C. Kak and Malcom Slaney. Principles of Computerized Tomographic Imaging. Ed. by Robert E. O’Malley. SIAM, 2001, p. 327. ISBM: 089871494X.
- Johann Radon. Über die Bestimmung von Funktionen durch ihre Integralwerte längs gewisser Mannigfaltigkeiten. Tech. rep. Leipzig: Berichte über die Verhandlungen der Königlich-Sächsischen Gesellschaft der Wissenschaften zu Leipzig, 1917, pp. 262–277.
- R A Crowther, D J DeRosier, and A Klug. The Reconstruction of a Three-Dimensional Structure from Projections and its Application to Electron Microscopy. In: Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences 317.1530 (1970), pp. 319–340. doi: 10.1098/rspa.1970.0119.
Obtaining radontea¶
If you have Python and numpy
installed, simply run
pip install radontea
The source code of radontea is available at https://github.com/RI-imaging/radontea.
Citing radontea¶
Please cite this package if you are using it in a scientific publication.
This package should be cited like this (replace “x.x.x” with the actual version of radontea that you used):
cite
Paul Müller (2013) radontea: Python algorithms for the inversion of the Radon transform (Version x.x.x) [Software]. Available at https://pypi.python.org/pypi/radontea/
You can find out what version you are using by typing (in a Python console):
>>> import radontea
>>> radontea.__version__
'0.1.4'