# Understanding the maths of Computed Tomography (CT) scans

**R-Bloggers – Learning Machines**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Noseman is having a headache and as an old-school hypochondriac he goes to see his doctor. His doctor is quite worried and makes an appointment with a radiologist for Noseman to get a CT scan.

Because Noseman always wants to know how things work he asks the radiologist about the inner workings of a CT scanner.

The basic idea is that X-rays are fired from one side of the scanner to the other. Because different sorts of tissue (like bones, brain cells, cartilage etc.) block different amounts of the X-rays the intensity measured on the other side varies accordingly.

The problem is of course that a single picture cannot give the full details of what is inside the body because it is a combination of different sorts of tissue in the way of the respective X-rays. The solution is to rotate the scanner and combine the different slices.

How, you ask? Good old linear algebra to the rescue!

We start with the initial position and fire X-rays with an intensity of 30 (just a number for illustrative purposes) through the body:

As can be seen in the picture the upper ray goes through areas 1, 2 and 3 and let’s say that the intensity value of 12 is measured on the other side of the scanner:

or

The rest of the formula is found accordingly:

We then rotate the scanner for the first time…

…which gives the following formula:

And a second rotation…

…yields the following formula:

Now we are combining all three systems of equations:

or written out in full:

Here is the data of the matrix for you to download: ct-scan.txt).

We now have 9 equations with 9 unknown variables… which should easily be solvable by R, which can also depict the solution as a gray-scaled image… the actual CT-scan!

A <- read.csv("data/ct-scan.txt") b <- c(18, 21, 18, 18, 21, 9, 18, 14, 16) v <- solve(A, b) matrix(v, ncol = 3, byrow = TRUE) ## [,1] [,2] [,3] ## [1,] 9 9 0 ## [2,] 9 5 7 ## [3,] 9 9 0 image(matrix(v, ncol = 3), col = gray(4:0 / 4))

The radiologist looks at the picture… and has good news for Noseman: everything is how it should be! Noseman is relieved and his headache is much better now…

Real CT scans make use of the same basic principles (of course with a lot of additional engineering and maths magic )

Here are real images of CT scans of a human brain…

… which can be combined into a 3D-animation:

Isn’t it fascinating how a little bit of maths can save lives!

**leave a comment**for the author, please follow the link and comment on their blog:

**R-Bloggers – Learning Machines**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.