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In scanning electron microscopy, the achievable image quality is oftenlimited by a maximum feasible acquisition time per dataset. Particularly withregard to three-dimensional or large field-of-view imaging, a compromise mustbe found between a high amount of shot noise, which leads to a lowsignal-to-noise ratio, and excessive acquisition times. Assuming a fixedacquisition time per frame, we compared three different strategies foralgorithm-assisted image acquisition in scanning electron microscopy. Weevaluated (1) raster scanning with a reduced dwell time per pixel followed by astate-of-the-art Denoising algorithm, (2) raster scanning with a decreasedresolution in conjunction with a state-of-the-art Super Resolution algorithm,and (3) a sparse scanning approach where a fixed percentage of pixels isvisited by the beam in combination with state-of-the-art inpainting algorithms.Additionally, we considered increased beam currents for each of the strategies.The experiments showed that sparse scanning using an appropriate reconstructiontechnique was superior to the other strategies.

How should a fixed budget of dwell time be spent in scanning electron microscopy to optimize image quality?