I’m trying to create a pipeline to count and measure axons in a nerve cross section. I just can’t get it to identify objects correctly. I’ve tried a couple of pipelines from other help posts that were similar, but none of them have the full nerve cross section, and no matter how much I tweak them, I can’t get them to identify the objects that I want.
I tried identifying the nerve as a whole (so I could then mask the image), and it will put an outline around it, but won’t count it as an object. I’ve tried unmixing colors, greyscale, thresholding, and I just can’t get it to work. If I can get it to identify the myelin sheath, then I think I can get it to measure the inner axon bit, but I can’t seem to get that right. Either it’s breaking the myelin sheaths into too small pieces, or it’s identifying the outer membrane of the nerve as some of the myelin sheath. At this point, I’ve added so many modules, trying to get the right combination of things, that I’m just confusing myself and going in circles.
I would just like some advice on how I should approach this. I think the real difficulty lies in that the inner part of the axons is slightly darker, so getting it to threshold to exclude that, but still count some of the smaller/less bright cells.
Should I edit the image beforehand to just exclude everything but the axons (before even putting it in cell profiler), or is there some easier way that I’m missing?
Currently our lab has been using (Fiji is just) ImageJ to go through each image one by one (so clunky and time consuming), often needing to manually add/remove neurons to the count, and I was hoping to streamline things by creating a pipeline. That way, once we have all the images stitched, we can just add them to the pipeline and analyze them.
Below are all the pipelines I’ve attempted to use (including the one with a billion modules all trying to get the magic image) as well as the test image I’ve been using.