I acquired fluorescence images using stained brain tissue sections (25µm thick) with antibodies that targeted the marker of neuronal activation c-Fos. I also have an endogenous signal (thanks to Cre transgenic mouse lines, in green), that is characteristic of a cell population.
I want to colocalize the cells where I have both an activity signal (red signal) and the cell population marker (green signal).
However, I have a lot of images, so I need to normalize them to be able to do the same automatized counting.
I tried Iterative deconvolution because there’s a strong noise in my images, but I’m loosing intensity and information.
Do you have any tips to avoid this loss of intensity, or is it unavoidable with Iterative Deconvolution ? Do you know if the fact that I can’t use Iterative Deconvolution on RGB Pictures (because I need 8bit images for this preprocessing) is a source of infomation loss ?
Do you know a way of normalizing the image intensity, but also removing the background and enhancing the cell contrasts without loosing information (applying the less filters possible) ? Is Iterative Deconvolution normalizing the intensity (as well as enhancing the image properties?) I might use HALO for the counting, which mainly needs intensity normalization.
Do you think I should use another software than ImageJ (e.g IMARIS) for preprocessing, because ImageJ is not dedicated to the treatment of fluorescence confocal images ?
Thank you in advance for your help,