Computed Tomography Simulation Using the Radon Transform

This Demonstration illustrates computed tomography (CT). It applies the Radon transform on the selected image with a number of projection angles. Using the inverse Radon transform on the resulting Radon image shows that the reconstructed image starts to resemble the original image as the number of projection angles increases.


  • [Snapshot]


The larger the number of projections applied on the original image, the more accurate the reconstructed image becomes. In computed tomography, many projections of the object are first generated from different angles. Then filtered back-projections are applied to reconstruct a 2D image of the structure of a particular cross section of the image. This is the basic idea used in X-ray medical imaging.
The Radon transform and the inverse Radon transform (both added in Mathematica 8) are used to simulate this method. Up to 128 projections can be taken between . Then applying the inverse Radon transform on the resulting image gives the filtered back-projection image.
In this Demonstration, only one filtered back projection is used per projection. The magnitude spectrum of the reconstructed image (the inverse Radon image) is updated as more back projections are applied, showing that the spectrum approaches that of the original image. Ram–Lak and cosine ramp filters for inverse Radon transform generate the clearest reconstruction; however, streak lines appear across the reconstructed image; these do not appear in some of the other filters nor for the nonfiltered image.
The "n" slider represents the number of projections or angles to apply. The parameter is Mathematica's "CutoffFrequency" option for the inverse Radon. You can adjust the 2D frequency spectrum of the images for better viewing. A checkbox lets you change the view of the image magnitude spectrum from 2D to 3D. For original color images, a checkbox can be used to process the image in gray only, as processing the image in color requires more time and memory.
For more information, see the website on the window function and the author's report on computed tomography.
[1] A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging, New Brunswick, NJ: IEEE Press, 1988.
[2] H. Murrell, "Computer-Aided Tomography," The Mathematica Journal, 6(2), 1996 pp. 60–65.
    • Share:

Embed Interactive Demonstration New!

Just copy and paste this snippet of JavaScript code into your website or blog to put the live Demonstration on your site. More details »

Files require Wolfram CDF Player or Mathematica.

Mathematica »
The #1 tool for creating Demonstrations
and anything technical.
Wolfram|Alpha »
Explore anything with the first
computational knowledge engine.
MathWorld »
The web's most extensive
mathematics resource.
Course Assistant Apps »
An app for every course—
right in the palm of your hand.
Wolfram Blog »
Read our views on math,
science, and technology.
Computable Document Format »
The format that makes Demonstrations
(and any information) easy to share and
interact with.
STEM Initiative »
Programs & resources for
educators, schools & students.
Computerbasedmath.org »
Join the initiative for modernizing
math education.
Step-by-Step Solutions »
Walk through homework problems one step at a time, with hints to help along the way.
Wolfram Problem Generator »
Unlimited random practice problems and answers with built-in step-by-step solutions. Practice online or make a printable study sheet.
Wolfram Language »
Knowledge-based programming for everyone.
Powered by Wolfram Mathematica © 2018 Wolfram Demonstrations Project & Contributors  |  Terms of Use  |  Privacy Policy  |  RSS Give us your feedback
Note: To run this Demonstration you need Mathematica 7+ or the free Mathematica Player 7EX
Download or upgrade to Mathematica Player 7EX
I already have Mathematica Player or Mathematica 7+