Reduced-dose and high-speed acquisition strategies for multi-dimensional electron microscopy

Abstract

Multi-dimensional electron microscopy has recently gained considerable interest thanks to the advent of microscopes with unprecedented analytical and in situ capabilities. These information-rich imaging modes, though, are often subject to long acquisition times and large data generation. In this paper, we explore novel acquisition strategies and reconstruction algorithms to retrieve reliable reconstructions from datasets that are limited in terms of both per image and tilt series angular sampling. We show that inpainting techniques are capable of restoring scanning transmission electron microscopy images in which a very restricted number of pixels are scanned, while compressed sensing tomographic reconstruction is capable of minimising artefacts due to angular subsampling. An example of robust reconstruction from data constituting a dose reduction of 10× is presented, using an organic/inorganic core-shell nanowire as a test sample. The combination of these novel acquisition schemes and image recovery strategies provides new avenues to reduced-dose and high-speed imaging.

Development of a fast electromagnetic beam blanker for compressed sensing in scanning transmission electron microscopy

“…In order to discriminate shutter imperfections from reconstruction issues, we compare the reconstructed images with the reconstructions obtained from a virtually shuttered image obtained by applying a digital mask on the unshuttered experimental HAADF image as was typically done in papers discussing compressive sensing so far 13,14,25 . The results are shown in Figure 5, together with the reconstructed experimental images.…”

“…In order to overcome this issue, a wide range of different approaches are being tested in the TEM community like reduction of the kinetic energy of the fast electrons [1][2][3] , improving the detection efficiency of cameras [4][5][6][7] , time resolved approaches [8][9][10] and many more. Relatively recently, the concept of compressive sensing was proposed to significantly reduce the electron dose while maintaining all the important features in a TEM or Scanning TEM (STEM) image [11][12][13][14] . Compressive sensing is based on the assumption that an image contains a significant amount of redundancy and not all pixels in the image are independent.…”

Compressed sensing for dose reduction in STEM tomography

“…We compared our integrated framework for the reconstruction of randomly-downsampled STEM measurements to the prior approach proposed in [5].…”

“…Various methods have been developed to permit lower-dose 3D STEM acquisition without degrading the quality of the reconstructed volume. These techniques can be categorized according to whether the dosage reduction is achieved by angular downsampling or spatial downsampling [5].…”

“…The recovery of randomly-downsampled STEM images has been the pioneered work of a recent publication by Saghi et al [5]. The authors proposed to perform the reconstruction in two steps.…”