Image processing and Particle detection

Hello everyone,

This is my first post on here, I am hoping to get some comments on the technique I am using in Fiji / ImageJ so far. I have stacks of fluorescent confocal microscopy images. Each stack is a single time point and contains several slices.

So far I have done the following:

  1. Generate PSF using PSF generator (Richard & Wolf method)
  2. Deconvolute in Deconvlution lab (Richardson-Lucy algorithm)
  3. Aligment/Registration using StackReg (Affine transformation)
  4. Hysteresis connection thresholding
  5. Particle analyzer… to detect spots/specks/points

So here are a few questions:
-Where do smoothing and denoising fit in and how do I obtain parameters to quantify them.
-How do I quantify Hysteresis thresholding? (Otsu, Renyi Entropy, adaptive hysteresis…?)
-How do I align two stacks from different time points if they are also miss-aligned on the z plane by a slice or so

I don’t have a dark image that I can use to calculate SNR.

If you have any remarks about the techniques I am using, please let me know as it would be very helpful to me.

Sample screenshot from stacks:

Just a quick comment: the built-in Fiji plugin “Descriptor-based series registration (2d/3d + t)” will correct Z as well as XY shifts:

Thank you for your reply. I am having errors with this plugin. I could probably fix it. But when I use correct 3D drift, I get very unusual results. Not only the images are miss-aligned on every axis, there is a significant difference in the level of noise, and landmarks change drastically and disappear towards the lower slices. Is aligning stacks like these unrealistic if the data needs to be used to? (keeping in mind I need to align 3-4 time points)

outcome of alignment: