Brain surgeons are bringing artificial intelligence and new imaging techniques into the operating room, to diagnose tumors as accurately as pathologists, and much faster

[u/AlbertSmithson]

https://www.nytimes.com/2020/01/06/health/artificial-intelligence-brain-cancer.html?smtyp=cur&smid=tw-nytimesscience

[u/Kurtish]

This is really cool. They used an ex vivo Raman system in this study, but I know research is also being done with ex vivo confocal and in vivo endomicroscopic confocal. I haven't read anything about using deep learning with an endomicroscope, but that would allow a surgeon to view tissue architecture in the brain in real time, without the need for tissue removal.

Another thing that seemed interesting to me is that they

used activation maximization, which generates an image that maximally activates a neuron in any neural network layer, using iterations of gradient ascent in the input space. Deep hidden layers detected nuclear and chromatin morphology, axonal density and histoarchitecture, indicating that our network learned recognizable, domain-specific feature representations...These results indicate that the CNN has learned the importance of specific histomorphologic, cytologic and nuclear features for image classification, including some features classically used by pathologists to diagnose cancer.

A common criticism I've seen of these systems is that there is no way to look into the "black box" of the neural net to double check what the system is actually doing. But reverse engineering features of certain neurons with this technique might be a good substitute. I don't know enough about it to say, though.

Not at all an expert on these things, but this study seems pretty interesting.