Dear Dmitry,
what I've written has no direct relation to ImageJ but deals with a
method ("adaptive Wiener-corrected inverse filtering"), not a tool
(Image processing software; here "ImageJ").
The problem with real-world inverse filtering (reversing blur) is that
you need to find a compromise between image enhancement (inverse
filtering) and noise suppression (Wiener correction). If you don't care
about the latter, you will generate artifacts because filtered noise may
appear as supposedly relevant structures.
If you have a stack of images and its images (slices) show about the
same statistics, you need to do the S/N-analysis and the estimation of
the blurring function only for a single typical slice and you can apply
the same filter to all slices. Because the proper construction of a
"Wiener-corrected inverse filter" is costly, such situation is of great
advantage.
I hope this answers your question.
Regards
Herbie
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Am 29.11.24 um 10:53 schrieb Dmitry Semchonok:
Dear Herbie,
Thank you for your prompt response and helpful suggestions.
As I am relatively new to ImageJ, I have a follow-up question regarding
a related scenario.
What if one has a selected *.mrc stack of cropped cryo-EM particles
(e.g., liposomes) that have been corrected using a Wiener filter. Would
it be possible to use ImageJ to perform batch analysis and measure
different parameters on this stack?
Is it simplifying the problem?
Thank you for your time.
Kind regards,
Dmitry
------------------------------------------------------------------------
*From:* Herbie <[email protected]>
*Sent:* 28 November 2024 18:36
*To:* [email protected] <[email protected]>
*Subject:* Re: Inquiry on Analyzing Liposomes in Cryo-EM Images
Greetings Dmitry,
in order to be able to substantially provide some help, we need to see
typical images in a non-lossy file-format, preferably TIF .
"advice on how to address defocus in these images"
There is only one generic method which is "(adaptive) Wiener-corrected
inverse filtering". AI-approaches *at best* will produce comparable results.
Building good inverse filters is far from trivial because they strongly
depend on the individual image statistics (S/N-ratio):
<https://www.gluender.de/Writings/WritingsTexts/WritingsDownloads/1980_NoiseInDeblurring_scan.zip
<https://www.gluender.de/Writings/WritingsTexts/WritingsDownloads/1980_NoiseInDeblurring_scan.zip>>
Regards
Herbie
:::::::::::::::::::::::::::::::::::::::::::::
Am 28.11.24 um 19:16 schrieb Dmitry Semchonok:
Dear colleagues,
I hope this message finds you well.
I am seeking guidance on the proper methods for analyzing liposomes in
cryo-electron microscopy (cryo-EM) images. Specifically, I have some raw
cryo-EM images (*.mrc, *.eer) containing liposomes, and I would like to
determine their diameter, area, and circularity etc.
Is there a batch script available that can facilitate the measurement of these
parameters and assist in preparing the necessary statistics?
Additionally, I would appreciate any advice on how to address defocus in these
images.
Thank you for your assistance.
Kind regards,
Dmitry
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