This time we finally explains how it is possible to see inside object with x-rays.  (In this article it will be with example on industrial CT, which is slightly different from medical).

First of all it is needed to take a 2D picture. For that we need x-ray source - tube, detector and object we want to scan.  X-rays going from tube to detector are constant so whole picture is all same color. If we place object of interest between tube and detector,  some x-rays that go throught object are reflected or absorbed. That causes lower intensity on detector and we see this part darker. Every material has different absorbtion and thus we can see difference. Important is also thickness of material in the way of x- ray. 

http://www.rtg.fbmi.cvut.cz/rtgobrazky/absorpce.png
*X-Ray absorbtion [http://www.rtg.fbmi.cvut.cz]*

For tomography scanning we need only to take as many pictures possible in 360° . For example when we scan, we take pictures from up to 3400 different angles. To achieve that, object is placed in rotation axis (industrial) or tube and detector are rotating on gantra arount the object (medical).

http://www.qualitymag.com/ext/resources/NDT/June2015/ComputedTomography/Werth-Fig2_HighMag.jpg
*Rotating object [Werth Messtechnik Gmbh]*

https://www.microphotonics.com/wp-content/uploads/2015/04/micro-CT-rotation-principle.png
*Tube and detector rotating [https://www.microphotonics.com]*

All data colected are sent to computer workstation, where final picture is reconstructed.

![projekce.png](https://s22.postimg.org/eh6ejvkld/projekce.png)
*How final data is gained [CT-gurus]*

As you see on the picture, more images taken, better picture is in the result. Final reconstruction is done with variations on radons transformation algorithm and filtered backwards projection. Final data are voxels - volumetric pixels (3D pixel) with information about intensity of gray. From this data you can extract STL point cloud of surface.

http://ct-ndt.cz/useruploads/images/zakazkove-mereni-CT2.jpg
*On the left are tomography slices, on the right voxels*

http://ct-ndt.cz/useruploads/images/a2.jpg
*STL surface point cloud*

You can find more examples of results on our blog [@ct-gurus](https://steemit.com/@ct-gurus)

More about X-rays and results from CT, history and future next time

Previous posts:
[Part 2](https://steemit.com/life/@ct-gurus/basic-principes-of-computed-tomography-ct-part-2-detector)
[Part 1](https://steemit.com/life/@ct-gurus/basic-principes-of-computed-tomography-ct-part-1-tube)

RV