Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement



Nicholls, Daniel ORCID: 0000-0003-1677-701X, Wells, Jack, Stevens, Andrew, Zheng, Yalin ORCID: 0000-0002-7873-0922, Castagna, Jony and Browning, Nigel D ORCID: 0000-0003-0491-251X
(2022) Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement. Ultramicroscopy, 233. p. 113451.

[img] Text
6_updated_ULTRAM-D-21-00143_R1.pdf - Author Accepted Manuscript

Download (4MB) | Preview

Abstract

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this work, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

Item Type: Article
Uncontrolled Keywords: Bioengineering, Stem Cell Research, 4.1 Discovery and preclinical testing of markers and technologies, 4 Detection, screening and diagnosis
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 13 Jan 2022 11:49
Last Modified: 15 Mar 2024 10:27
DOI: 10.1016/j.ultramic.2021.113451
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3146464