Glad you found CellProfiler. Yes, you can do measure these, with caveats. If you could add a nuclear marker, that would help. The nuclei appear to be a little blue here (is that only DAB, or is there another marker here like Hematoxylin?). I have created a pipeline for you, assuming that:
(1) The nuclei are blue-ish in hue (and of course the cytoplasm are the typical brown DAB stain color)
(2) When you say, "percentage of positive nuclei", I am assuming you mean "blue-ish nuclei that also stain darkly for brown/DAB". Please clarify though, because it is not clear to me how you define "all nuclei" and "positive nuclei".
Side-note: Avoid JPG images because they are a lossy format. Try to save in, say, TIFF or PNG and no information should be lost via compression.
Look at my attached pipeline.
* UnmixColors is key for histological images. I added DAB, but also guessed at the blue-ish setting by adding our default Hemaoxylin. Feel free to change this to another setting but you need something to segment the nuclei with
* IdentifyPrimaryObjects: You will need to change the Threshold Correction Factor almost certainly. I changed this from 1 (default) to 2, but this may vary with staining parameters.
* IdentifySecondary: This seems to miss some brown regions, but that is because I am working under the model of "Define nuclei as small blue regions, and then grow out from those to the brown cytoplasm". If there is no blue-ish nucleus defined, there will be no brown Cell object.
* DisplayDataOnImage: This can be disabled (click the checkbox in the pipeline list) and is only to help you get a sense of the threshold applied in ClassifyObjects
* FilterObjects: This is only useful if you want to process the positive nuclei downstream (disable otherwise)
* ClassifyObject: This calculates the percentage positive
Hope that helps, and let us know if you need help in case I made some wrong assumptions.
DL_DAB.cppipe (11.9 KB)