Practice tomography with this portable Raspberry Pi-based kit

Behold Emanuel Larsson and his colleagues’ invention: a kitchen-based light tomography kit (KBLT) which uses Raspberry Pi 4 to scan both transparent and non-transparent objects in 3D and 4D.

tomography KBLT
Spot the Pi


Tomography is a way to look at the internal structure of an object (a cell, your brain, a priceless artefact that you suspect is a forgery) without cutting into it mechanically. There are lots of different types of tomography, but in general, you aim some kind of wave (X-rays, visible light, gamma rays…) at the object you want to investigate, and measure what gets through to the other side.

Different materials absorb and scatter waves in different ways, so by measuring what makes it through, you can figure out what’s inside and make a computer image of it. The beams of energy are aimed and focused in such a way as to investigate one slice of the object at a time, and either the beams or the object are rotated to allow you to look at once slice after another. Afterwards, you can make a computer model of the whole object by stacking the images of all the slices together.

How does it work?

KBLT uses a strong LED flashlight as a light source instead of using X-rays or neutrons. Below you’ll find a near-perfect example from Emanuel’s team of when an image is worth a thousand words. Well, six images and a table, but they show exactly what everything is and what it does.

A series of labelled figures A to G showing the KBLT tomography kit. The 1st LED light source and a differently located alternative 2nd source are shown, along with the sample mounted on a rotation stage, the detector screen, and the acquisition camera. Details of the stepper motor for sample translation, the power supply, and the connections between electronic components are also shown. There is also a screenshot of the GUI allowing the operator to adjust the setup.
Image from

One of two LED light sources shines a beam of light at the sample object, which is mounted on a stage that can rotate it and translate it (move it sideways). Light passing through the sample shines on a paper detector screen behind the sample, and a camera behind that takes photos of the light and shadow on the screen. There’s a touchscreen that provides a graphical user interface so the operator can adjust the setup.

What’s it for?

The KBLT scanner is ideal for training students and researchers in tomography using ordinary visible light. Then they know what they’re doing when they graduate to carrying out real X-ray or neutron tomography experiments. That equipment is expensive and in high demand, so it’s tricky to get enough practice with the real deal. The KBLT is portable too, so it can be ferried between different classrooms or even used in your own kitchen, hence its name.

The KBLT can scan transparent objects…
… and non-transparent objects

The KBLT’s ability to acquire datasets quickly can help researchers develop improved algorithms for reconstructing images from tomography data. Emanuel predicts the KBLT will be especially useful to beamline scientists who develop and maintain the highly specialised equipment that X‑ray and neutron tomography requires, helping them test and implement new hardware and software solutions when an X‑ray or neutron beam isn’t available. Computational researchers can also use it to test their algorithms on easily generated KBLT datasets.

Tomography for all

All the software for motor control, image acquisition, and image reconstruction and analysis is open source and available on GitHub.

Emanuel and his team’s work has been published in the Journal for Tomography of Materials and Structures and is also open access for all. You can read the whole thing here.

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Andrew Buckley avatar

I could have used something like this over 20 years ago to help me get a grip with the mathematics of tomography as opposed to having to use a similarly Heath-Robinson esque x-ray based system (that took 2 hours plus per scan).

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Ashley Whittaker avatar

But think of the MEMORIES Andrew

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