I’ve been using CP to perform object ID based on staining of cells. As an output of this pipeline I have the objects converted to RGB images where each color corresponds to an object class. Once a stack of theses is finished I like to go through them and correct any false positives in photoshop. (please see attached image)
Once the images are corrected, I’d like to re-process them with CP to map them out in XYZ as well as other measurements like size etc. If I load the image as objects - it is able to ID the objects but clumps all three classes into one. It seems the only way to do this would be to load them as images - split the RGB image, then re-identify the objects from scratch either using Apply Threshold + binary or straight into ID primary objects with manual .1 or something - This is rather inefficient though as the channels are essentially binary and reprocessing a stack can take many hours on a high performance machine due to the very high resolution of the images.
Is there a better way to do this? It seems surprising to me there isn’t a “convert image to objects” module I can use after splitting the RGB image. I’m not complaining by a stretch as CP is already an amazing software that is extremely useful for my work but I had to assume there’s something wrong with my perception or knowledge of CP before accepting this isn’t possible…
either way, many many thanks for producing a fantastic piece of software and your continued development and support!!!