Measure cilia beating frequency

Hello,

@VolkerH @DimaD @Alex_H

We would like to quantify the beating frequency of cilia in images like this:

4_016-1

I have already some code in ImageJ that would probably allow to do this:

But I was wondering whether other people also have some code? Maybe to share efforts and experiences…

Thanks!

I have done something similar for Marko a couple of years back. However, the repo contains users’ data so I can’t share it here as is (needs some cleaning up). Will send you an email.

Edited to add: that this was mainly based on the scipy.signal.periodogram function (so not in the ImageJ ecosystem).

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Naively I’d have chosen a kymograph-based approach such as:

  • Draw a line at the “edge” of the cilia:

    image

  • Image > Stacks > Reslice… without interpolation:

    image

  • Analyze > Plot Profile on a line in the region of interest:

    image

… which gives me a periodicity of roughly 35 frames as a “quick and dirty” guess.

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@Christian_Tischer didn’t tag his post #imagej, so I guess he was explicitly open for solutions in any software ecosystem, right?

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Yes, this is correct, e.g. a python notebook solution would also be interesting.

Maybe all you need is just one more step of FFT to make it clean ?

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Regarding a Java based solution, does someone know examples where this code is already being used?
@imagejan

AFAICT, the fft ops (implemented by @bnorthan mostly) are using this code:

The ops tutorials on FFT are still incomplete, but @gselzer is working on them, I think.

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Nice! Do you happen to know whether it also works on 1D data? As imglib2 is N-dimensional it should, or?

Let’s just try it (in Groovy):

#@ Img input
#@ OpService ops

histogram = ops.run("histogram", input)
fft = ops.run("fft", histogram)
println fft.firstElement()

On the Blobs sample image, this gives:

(65024.0) + (0.0)i

… which means it worked technically. Of course running FFT on the histogram might not make much sense here, but I was taking net.imglib2.histogram.Histogram1d as a simple example of a 1D Img.

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Hi @Christian_Tischer

There is an example showing use of imagej-ops FFT in the script editor under “Templates->Tutorials->Find Template.py”. The only weird thing is that it no longer runs as is, and you have to change the last two input from ImgPlus to Dataset.

It might be useful because it shows how to visualize the real and complex parts of the FFT and use it to find a template. It’s based on a previously existing imglib2 tutorial.

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Thanks for pointing to the template!

For me, it was running fine as is in an up-to-date Fiji (after running the Crop Confocal Series tutorial first).

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