Thanks so much for the suggestions. I am not exactly sure what the best threshold factor is but tried a range 0.7, 1, 1.3 and 1.5. See the attached figure. I think it looks pretty good now.
Anyway, while I did this some other things came up - when I set the threshold correction to 1.3 on the negative image I got an error message that said " negative row index found" and then CellProfiler asked me if I wanted to continue the analysis. Any idea what this refers to? This was for the negative image only. Also, on the negative set where I used 0.7 as a threshold I end up with a totally blue square where it is supposed to relate my spots to the cells - I see this occasionally but have not quite figured out why that is.
Also in the previous message you said: " The fact that included a negative control image is helpful since you now have an idea of what the noise level looks like in the absence of spots. You can set the lower bound on the threshold to an appropriate value by seeing what pixel values are typical for these negatives, and make sure that no/minimal objects are detected in the negatives (which already seems to be mostly the case) and the spurious objects are missed in the positives."
I have not quite figured this out - this is why I was not sure I should say rescale intensities when loading the images (although that makes no difference to my spot counting). When I open my negative image in CP I expect it to be completely black but instead I see this vague cell look - as one sees when the brightness and contrast is greatly adjusted - it is not real. Thus I don’t know how to set the lower bound on the threshold based on the pixel values. Do I go with those values that I can see on the image? It seems to be about 0.04 - is this the background you where referring to?
Thanks for all the help and suggestions!