I want to count the percentage of ki67-positive tumor cells in tumor tissue that also contains stroma. For this I plan to use the (1) cell detection and then (2) create annotations in order to train a classifier based on those annotations.
My problem is the cell detection of ki67-stained tumor cells. Many tumor cells have a dot-like, punctate nuclear stain patten, which necessarily isn’t to be considered as positive, however, many of them are not identified at all by the detection tool. Also many negative tumor cells are not identified adequately. Stroma cells are picked up more easily.
I read that optical density sum is recommended in situations with punctate nuclear staining patterns. I have tried to adjust the nucleus-, cell- and general parameters extensively but just can’t get it identify all tumor-negative and tumor-positive cells. I intend to use a single threshold. I use default stain vectors.
Here is part of the original image. Tumor cells are morphologically easy to distinguish from stromal cells.
Here the detection. Many tumor cells (positive and negative) are not encircled properly.
Threshold seems right as far I can see
I’m using 0.2.0-m8 version.
Thanks in advance!