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'