Here are a few ideas for your pipeline.
CellProfiler can definitely make these types measurements.
I often take this approach when working with image sets. I’ll use whatever channels are optimal to create “cell” objects but then I’ll measure multiple channels within those cells. For example, I might use the nuclear stain and a cytoplasmic stain to create an object that demarcates where the cells are, but then I’ll make measurements for other channels within those cells.
In your pipeline, for example, if the MAB22FinalCell object accurately captures the cell objects that you’re interested in, you don’t need to create a FOUR321FinalCell object in order to measure intensity for the Four321 channel within the cells. You can use a single MeasureObjectIntensity module to measure both channels within the MAB22FinalCell objects.
It’s possible that you could create a workflow to detect these regions automatically, if there is a way to distinguish the unwanted regions from cell objects (such as by size, intensity, etc.).
In general, this tutorial may be useful for you: I2K 2020 tutorial: Introduction to Image Analysis and Machine Learning With CellProfiler and Cell... - YouTube. The biological problem is different, but the principles of how to build a pipeline and create and measure objects are the same.