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Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

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

Daniel Nicholls¹, Jack Wells², Andrew Stevens³

¹Department of Mechanical, Materials and Aerospace Engineering, University of Liverpool, Liverpool, L69 3GH, United Kingdom.

Ultramicroscopy

|December 16, 2021

Summary

This summary is machine-generated.

Sub-sampling in scanning transmission electron microscopy (STEM) speeds up image acquisition and controls electron dose. This study optimizes image reconstruction parameters for enhanced resolution and sensitivity in STEM imaging, offering open-source tools for broader application.

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Area of Science:

Materials Science
Microscopy Techniques
Computational Imaging

Background:

Sub-sampling in scanning transmission electron microscopy (STEM) enhances acquisition speed and dose control.
Image reconstruction is crucial for recovering high-quality data from sub-sampled datasets.

Purpose of the Study:

To investigate the impact of reconstruction parameters on image inpainting in STEM.
To optimize these parameters for improved resolution, precision, and sensitivity in STEM images.
To provide open-source tools for parameter testing and application.

Main Methods:

Utilized beta-process factor analysis (BPFA) for image inpainting.
Developed and demonstrated a method for optimizing sub-sampling and reconstruction parameters in STEM.
Created an open-source code package and tutorial for parameter testing.

Main Results:

Parameter selection significantly affects the quality of inpainted STEM images.
Optimized parameters lead to enhanced resolution, precision, and sensitivity.
The developed method is applicable to any STEM dataset.

Conclusions:

Optimized sub-sampling and reconstruction offer a powerful approach for STEM imaging.
This method has significant implications for imaging beam-sensitive materials and dynamic processes.
Open-source availability facilitates wider adoption and further research.