I’m trying to use QuPath’s pixel classifier to identify various tissue types (fibrous, smooth muscle, calcification, lipids etc.) in MT-stained histology slides of blood vessel plaque. My image type is set to “brightfield other.” To train the classifier, I have been manually drawing annotations for each tissue type/class on the slide, with the number of annotations per tissue type ranging from 3 to 25.
My current challenge is that I’m struggling to get the pixel classifier to distinguish between two tissue types (lipids and smooth muscle cells) that both appear as light purple/magenta regions, despite increasing the number of annotations and even loading training annotations from multiple slides. Since I know that lipids are more likely to be found in one part of the slide and less likely to be in other parts, is there a way to tell the pixel classifier where to look for a particular tissue type, or identify general regions that DO NOT contain a particular tissue type? Or is my best bet simply to increase the number of training annotations and hope the rate of misclassification decreases? Are there any image settings that would improve accuracy on Masson’s trichrome specifically?
I’m fairly new to QuPath, so any pointers and suggestions would be greatly appreciated!