One way you could aproach this using also a simple macro without much programming is: You have a spots in the image somewhere and want to get a defined radius around that spot and then get ROIs that are separated when they are touching. In practice, we’ve been unable to make it work.Īs far as I understood now. In principal I know what we need - region growing + collision detection.
In addition, if two ROI’s “collide” we’d like the overlapping region to be divided between them. 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. The output is a list of x/y coordinates for the centroid of each nucleus. We have scripted the automated segmentation/detection of the nuclei, which works very well. This is as accurate as manual scoring, but we would like to automate it further as it is still overly laborious. 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. 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. We are trying to macro an automated analysis of large immunofluorescent images of tissue sections 4-6 colours/image.
