I have been working on the following pipeline (attached) and found that I had to keep adjusting the settings (IDPrimaryObject) for each round of experiments. The minimum desired final output is CellCount and I am trying to create a pipeline for the lab to use repeatedly.
My guess is that the variation in settings is due experimental variation ranging from shRNA transfection efficiency (changing exposure which thus changes the signal:noise ratio), microscope lamp intensity variation, plate/well shape (shadows), number of cells plated, and any other numerous variables. Additionally the fluorescent scope that is being used is not the best for imaging.
To account for uneven lamp and false positives, I added in an illumination correction calculation and apply (done for each image). This helped greatly, but then I found that I was missing some cells despite how much I played with the IlluminationCalculation or the IDPrimObjects module.
I just added a RescaleIntensity to help me pick up the cells that were not being counted. I found that this was worse in the images that needed a longer exposure. I am not 100% sure how the module works, however after some trial and error have gotten much improved results.
However, I am still struggling with clumping. I am wondering if there is anything else that can be done to help with this? Or, would it be better to fix the lamp issue and the missing objects issue by ways that would make de-clumping easier? Or, is it not feasible for CellProfiler to declump that well?
Note: in the images attached below there are small uniform dots. Those are not cells, those are the fluorescent light shining through the pores of the well insert. Thus, I have set the bottom size limit in the IDPrimary to not measure them.
Thanks in advance!
BloodBrainBarrier16X_05272010.cp (8.07 KB)
Image with “missed” cells before the rescale was added
Image with clumping (extreme case)