I'm sorry, I think I mis-read what you were attempting to do; thanks for your patience. I'm attaching a pipeline which idenitfies the features you're looking for. The one main addition is the use of the Exclude module, to get rid of objects outside the red cell mask. Also, I changed the thresholding method for the red cells to Otsu global and adjusted the correction factor, as well as the segmentation settings for the blue/green cells.
Re: Multi-channel processing - The ColorToGray module can handle up to 3 channels per image, i.e., RGB. Any more than that, will require multiple image files. The easiest solution is to output your image data as individual grayscale images, one for each channel, and use LoadImages to proceed each set of N channels.
re: Resolution - The answer to depends on how well your pipeline is identifying the features that you want. If you find that that very small dim objects are unable to be detected regardless of how you tweak the settings, you may need to increase the resolution. For a simple cell count, you can probably still achieve good performance with smaller images. However, if you are interested in morphological measurements, then the image resolution will be more of an issue.
In any case, as mentioned earlier, remember to change the size-dependent settings if you choose to change the resolution. For example, the same settings could not be used on the Test1 and Test2 images, since the resolution is different; since Test3 is about half the resolution of Test1, the size settings in IDPrimAuto and SmoothOrEnhance had to be reduced by half as well, which is what the pipeline is set to.
Hope this helps!
2010_01_29_PIPE.mat (1.8 KB)