We are trying to macro an automated analysis of large immunofluorescent images of tissue sections; 4-6 colours/image. We’re not trying to segment out individual cells perfectly, but rather are looking to score the presence or absence of 3-5 markers/cell. Our approach, which works when done semi-manually, is to generate a point-list of cell centroid positions, based on nuclear staining, and then to draw a circle around each centroid which is then used as an ROI for the other channels. This is as accurate as manual scoring, but we would like to automate it further as it is still overly laborious.
We have scripted the automated segmentation/detection of the nuclei, which works very well. The output is a list of x/y coordinates for the centroid of each nucleus. What we’d like to automate is a simple form of region growing - basically, we want to generate automatic circular ROI’s of a user-set diameter centred on each centroid. In addition, if two ROI’s “collide” we’d like the overlapping region to be divided between them. In principal I know what we need - region growing + collision detection. In practice, we’ve been unable to make it work.
Any advice is welcome.