in scientific image processing workflow, a common task following image segmentation is to determine the amount of overlap between objects that were segmented from different sources, for example:
- determining double-positive cells from segmentations of two markers, or
- “sanitizing” ground-truth segmentations of time lapse images, such that the same objects have the same labels in different frames (whereas they might have a random label when the frames were segmented independently);
(this second point classifies as a tracking problem, but is actually simpler than most tracking problems when the objects are large and the movement between frames is small)
In both cases, it’s not enough to simply determine if two labels overlap (a measurement provided by the Segment Features node and others), but we actually need to know by how much they do.
The Compare Segments node seems to be able to do this, but (as far as I understood) compares each target segment to all reference segments and so requires looping over frames e.g. when working with time lapse images.
I feel like I must be missing something.
Are there any example workflows available demonstrating the task of computing the pairwise overlap between two (or more) groups of label instances?