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Feature adaptive sampling for scanning electron microscopy

  • 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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Document Type:Article
Author:Tim DahmenORCiD, Michael Engstler, Christoph PaulyORCiD, Patrick TrampertORCiD, Niels de JongeORCiD, Frank MücklichORCiD, Philipp SlusallekORCiD
Parent Title (English):Scientific Reports
Year of first Publication:2016
Release Date:2022/11/18
Impact:04.259 (2016)
Funding Information:European Research Project NOTOX (FP7-267038), the DFG grant IMCL (AOBJ: 600875) and the “Landesforschungsförderungsprogramm des Saarlandes” (WT/2-LFFP 15/09). The authors thank the DFKI GmbH and Saarland University for additional funding and for providing the necessary infrastructure and E. Arzt for his support through INM.
Groups:Innovative Elektronenmikroskopie
Open Access:Open Access
Signature:INM 2016/43
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International