Machine learning is supposed to help us do everything these days, so why not electron microscopy? A team from Ireland has done just that and published their results using machine learning to enhance STEM — scanning transmission electron microscopy. The result is important because it targets a very particular use case — low dose STEM.
The problem is that to get high resolutions, you typically need to use high electron doses. However, bombarding a delicate, often biological, subject with high-energy electrons may change what you are looking at and damage the sample. But using reduced electron dosages results in a poor image due to Poisson noise. The new technique learns how to compensate for the noise and produce a better-quality image even at low dosages.
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