I totally agree with Mark for a CP-only solution. But another approach is to try ilastik and train a pixel classifier to learn your bright-field objects! Please see Mark’s nice description here of ilastik and how to use it with CP: Select Region Based on Texture
Here’s a sample training set using your image (which took all of 5 minutes to generate): cl.ly/image/2M2R3Y3j1x3z
And here is the ilastik segmentation output: cl.ly/image/2G1Y2534260S
You can then input the ilastik probability maps into CP’s ClassifyPixels (in Windows only) and use it to seed a better segmentation in CP’s standard Identify* modules.
Side-note: Your image is 32-bit RGB, which is likely unnecessarily big. This will slow down CP and ilastik (or anything else). Try saving at a bit depth of 16 (max), as well as grayscale unless you’re sure there really is some color info or extremely fine intensity gradients of biological relevance here.