Dear Herbie, Thank you for your insights and clarification. I appreciate your explanation of the adaptive Wiener-corrected inverse filtering method.
I will return with actual data in hand to explore the analysis further. Thank you for the conversation. Kind regards, Dmitry ________________________________ From: Herbie <[email protected]> Sent: 29 November 2024 10:52 To: [email protected] <[email protected]> Subject: Re: Inquiry on Analyzing Liposomes in Cryo-EM Images 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 ::::::::::::::::::::::::::::::::::::::::::::: 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 > > -- > ImageJ mailing list: http://imagej.nih.gov/ij/list.html > <http://imagej.nih.gov/ij/list.html> -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html -- ImageJ mailing list: http://imagej.nih.gov/ij/list.html
