Tissue annotation and spatial measurements

Practice

5. Automating tissue annotation

   1. Pixel-based classification

      1. Create a pixel classifier on the TRITC channel and apply it with default parameters.

         • What is the area of the annotated region?

      2. Adapt the parameters of the pixel classifier to yield coherent regions.

         • How does the area of the annotated region change with smoothing sigma?

         • How does the area of the annotated region change with intensity threshold?

   2. Machine learning pixel classifier

      1. Based on what you have learned by creating a machine learning classifier for cell objects, create training annotations for whole regions (akin to tissues) using the paint brush.

      2. Train a pixel classifier on these training data to identify regions of high signal intensity in the TRITC channel.