aksg87:

so there isn’t the notion of oversampling the individual images (or "slices)


So you cannot feed 3d cropped data? This can, of course, happen as UNets have a minimum input size. But then, maybe your data is less imbalanced than I thought.
In addition to thresholding on the probability distribution, smoothing the shape through morphological operations (dilation/erosion) and throwing out detection sites below a size threshold seem common postprocessing steps, too. We discuss some of that in chapter 14 of the book.
One of the crucial things in practice is to have a rigorous evaluation pipeline for experiments early on. I must admit that the ideaexpreased in the paper of comparing different tasks based on the respective dice score the achieve makes me a bit uncomfortable. One may come to the conclusion that the objective function does not work well on some tasks, but there also is a trap in mixing exploration and evaluation too much. Or maybe I’m just grumpy today. 
Best regards
Thomas