[a-dub]

the primary innovation is using deep learning to denoise the signal and the cost savings derived from being able to use a noisier signal.

whether you call it "SnR improvement" or "additive noise cancellation", it is undeniably adulteration of the signal.

looking at the supplementary information, it looks like this paper was reviewed by mr-physicists. i think it also should have been reviewed by ml experts as well.

[heartbeats]

Sure, but it's not like it has the potential for overfitting. From my layman's understanding, the process is this:

1. Measure outside interference sources 2. Measure MRI of "nothing" 3. Use ML to estimate f(interference) = noise 4. Subtract estimated noise from signal

So the noise removal process has no awareness of brains, skeletons, etc.