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.

Obtaining radontea

If you have Python and numpy installed, simply run

pip install radontea

The source code of radontea is available at

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):


Paul Müller (2013) radontea: Python algorithms for the inversion of the Radon transform (Version x.x.x) [Software]. Available at

You can find out what version you are using by typing (in a Python console):

>>> import radontea
>>> radontea.__version__