Thanks a lot for the input! I spent much time with ImageJ and CellProfiler, trying all kinds of features and modules to get the results I’d like to have. I managed to make some progress, but right now, I’m at some point where I’m running out of ideas.
I took your advice and tried the ClassifyObjects Module. However, there are a lot of clumped objects that do not get separated properly, so the result would be false in the first place. The classifying works ok. I have two populations: (high intensity, low area = Macrophages; low intensity, high area = VSMC) How can I assign the other 2 “false” populations to another one? For example, I got several MPHs, which are slightly dimmer and end up as LOW-LOW. On the other hand, I have many HIGH-HIGH Objects, since CP doesn’t separate some of the clumped MPHs. The pipeline which uses the ClassifyObjects module isn’t working right now, but I included it nonetheless.
After all, I had the feeling, that the results were better when I separated both nuclei by size in the first place. By enhancing the contrast and playing with the size cut-off, I managed to get a decent algorithm. The problem I have right now is the fact, that a watershed doesn’t seem enough to separate between clumped nuclei. I tried enhancing the pictures with ImageJ (different contrast, manual tresholding and converting to binary pictures, enhance edges, add/ subtract/multiply features, eliminating the background, running watershed, etc …) On one hand, even with manual tresholding and a watershed filter it is not possible to separate the nuclei properly, so I am not sure if simple tresholding will be enough for my project. On the other hand, I have problems running the ImageJ module. Although I have written a few simple, working Macros and ImageJ is running in my pipeline, the pictures are not edited. Is that a bug??? (So I edited the pictures myself for now). Furthermore, I get an error when I try to load a binary image from ImageJ (It is still an 8bit image, but the values are only at 1 and 255). How do I solve that?
Identifying the Alpha Actin positive cells seems to be a challenge as well. The cells are not round, differ in shape and size and the intensity varies since the staining is complicated and not every cell is stained perfectly. Here I see the same problem: Treshholding doesn’t seem to be sufficient to fit my needs. Is there a way to implement some sort of directional information of the actin fibres for example? By the way, I tried identifying the VSMC as primary objects as well. The results are not better, maybe even worse, since the input from the nuclei is missing.
Last but not least, I wondered if there are people in Germany or even my State or city that use cellprofiler as well. Being able to talk to someone who is experienced in handling this program might be a great help, considering I am doing everything from scratch on and rely on handbooks, papers and your online support You ask for personal information on your download page. Do you think you could help me out with contacts?
I know, that’s a lot of information and issues that I got, but I think the CellProfiler will be a tremendous help once I have a running pipeline. I can’t thank you enough for your help and support!
PS: I included my current pipelines, the images and my ImageJ Macro in the zip file.
CellProfiler - MR.zip (2.85 MB)