I am interested in analyzing a complex tissue and have found the cell detection and then object classifier to be quite successful. However, in my tissue there are regions where the nuclei are sparse and increasing the cell expansion only causes more miss identification downstream. Also, i want to eventually quantify all of the space on the tissue, not just that what is near a nuclei. It seems to me that running the cell detection and then running the SLIC (or similar process) to “fill in” the remaining space with objects could be useful for the detection classifier. Can this be done?
I have attached an image of my tissue and an annotated version of the 4 areas i want to be able to eventually classify.
Any help is greatly appreciated!