I’m struggling these days trying to find a good way to turn 3D binary semantic segmentation masks into instance segmentation masks. The data I’m working on is 3D C. elegans data, I got the binary semantic segmentation masks with 3D U-Net. But I find it is very hard to turn these binary masks into instance masks.
I’ve tried watershed postprocessing (watershed on smoothed Euclidean distance transform), but the result is very ugly, with many oversegmented or unsegmented cells (see attached), though I’ve explored many parameters in the watershed pipeline. I’m wondering if there are better ways to convert these binary masks into instance masks.
Any help/advice would be appreciated! Thanks very much!
t162.tif (1.0 MB)t162_watershed_segmentation_8bit.tif (8.0 MB)