LECTURE NOTES IN MEDICAL ENGINEERING

X-Rays: Wave or Particle — Enter the Dark-Field

Phase-Contrast X-ray Imaging

Andreas Maier
22 min readMar 18, 2022

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These are the lecture notes for FAU’s YouTube Lecture “Medical Engineering”. This is a full transcript of the lecture video & matching slides. The course is supported by a corresponding Open Access Book, and Open Source Slides (zenodo/github). We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you spot mistakes, please let us know!

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Welcome back to Medical Engineering. So today we want to talk a little bit about a new kind of modality. This is called X-ray phase-contrast imaging. So in the following video, we want to talk a bit about whether X-rays are particles or, waves. We’ll see that there are also wave characteristics that we can use to determine phase contrast and related contrasts. So looking forward to exploring a little bit more of X-ray physics with you guys.

Image from the Medical Engineering lecture under CC BY 4.0.

So we start with a little motivation. Let’s have a look at what we can find with the phase-contrast images.

Image from the Medical Engineering lecture under CC BY 4.0.

So this is the absorption image. So you’ve already seen that for quite some time and we know that this is essentially just the absorption effect just a regular X-ray image. You see that we see bones here very well and this is a mouse that you can see here in this image. But there’s more to that. There is the so-called differential phase and this is measuring the phase shift and here we get a very different contrast and to be honest we get a derivative with respect to x-direction that is reconstructed. You see that we see the very fine structures here in the lung. Yet we have a third modality here and the third modality is the so-called dark-field image. This is a very different contrast than…

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Andreas Maier

I do research in Machine Learning. My positions include being Prof @FAU_Germany, President @DataDonors, and Board Member for Science & Technology @TimeMachineEU