“Segment anything” works considerably better than “Remove background” function in PowePoint and it is nice that it is made easily accessible in a web application and that the training data is published as well. But I don’t really get the excitement about using it for medical images.
To me it its performance seems to be comparable to 20-year-old classic Watershed segmentation, but Watershed can be used in 3D as well. See a simple comparison on an easy segmentation problem:
SegmentAnyhing is simpler and more convenient in that you don’t need to switch between effects, segments, etc. But even with the inconveniences of switching between effects, segments, etc. the overall task completion time is comparable. Updates take a bit longer in Slicer, as in Slicer we update a 3D segmentation consisting of 9 slices, while SegmentAnything just segments only 1 slice.
MONAILabel also has similar interactive neural network based tools (deepedit, etc.) that are supposed to work much better, because they are trained on medical images and some of them can also work in 3D.
For me, the main conclusion is that we need to make Slicer’s segmentation tools simpler to use and make more people aware that they exist.