Feature Adaptive Sampling for Scanning Electron Microscopy

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Date
2016
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Publisher
[London] : Macmillan Publishers Limited, part of Springer Nature
Abstract

A new method for the image acquisition in scanning electron microscopy (SEM) was introduced. The method used adaptively increased pixel-dwell times to improve the signal-to-noise ratio (SNR) in areas of high detail. In areas of low detail, the electron dose was reduced on a per pixel basis and a-posteriori image processing techniques were applied to remove the resulting noise. The technique was realized by scanning the sample twice. The first, quick scan used small pixel-dwell times to generate a first, noisy image using a low electron dose. This image was analyzed automatically and a software algorithm generated a sparse pattern of regions of the image that require additional sampling. A second scan generated a sparse image of only these regions, but using a highly increased electron dose. By applying a selective low-pass filter and combining both datasets, a single image was generated. The resulting image exhibited a factor of ≈3 better SNR than an image acquired with uniform sampling on a Cartesian grid and the same total acquisition time. This result implies that the required electron dose (or acquisition time) for the adaptive scanning method is a factor of ten lower than for uniform scanning.

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Keywords
tomography, beam, damage, tilt, cells
Citation
Citation
Dahmen, T., Engstler, M., Pauly, C., Trampert, P., de Jonge, N., Mücklich, F., & Slusallek, P. (2016). Feature Adaptive Sampling for Scanning Electron Microscopy (Version publishedVersion, Vol. 6). Version publishedVersion, Vol. 6. [London] : Macmillan Publishers Limited, part of Springer Nature. https://doi.org//10.1038/srep25350