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3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

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Improving the depth resolution of STEM-ADF sectioning by 3D deconvolution.

A Ishizuka¹, K Ishizuka¹, R Ishikawa^2,3

¹HREM Research Inc., 14-48 Matsukazedai, Higashimatsuyama, Saitama, Japan.

Microscopy (Oxford, England)

|October 13, 2020

Summary

This summary is machine-generated.

This study introduces new deconvolution methods for scanning transmission electron microscopy (STEM) annular dark-field (ADF) images, improving 3D atomic localization. These techniques enhance depth resolution for precise 3D imaging of single atoms and materials.

Keywords:

3D deconvolution Richardson–Lucy algorithm STEM-ADF depth resolution maximum entropy method (MEM)optical sectioning

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Published on: March 12, 2017

Area of Science:

Materials Science
Microscopy
Computational Imaging

Background:

Three-dimensional (3D) atomic localization using scanning transmission electron microscopy (STEM) remains challenging despite advances in aberration correction.
Improving depth resolution in STEM imaging is crucial for understanding nanoscale material structures.

Purpose of the Study:

To develop and validate novel 3D deconvolution routines for STEM-annular dark-field (ADF) through-focus images.
To enhance the depth resolution and enable precise 3D localization of single atoms and thin material layers.

Main Methods:

Developed deconvolution algorithms based on the maximum entropy method (MEM) and Richardson-Lucy algorithm (RLA).
Applied these routines to through-focus STEM-ADF image series, utilizing 2D and 1D convolution strategies.
Validated methods using simulated STEM-ADF images of Ce dopants in AlN and experimental images of graphene.

Main Results:

MEM deconvolution clearly localized Ce dopant peaks in depth, reducing peak width by approximately 50%.
RLA deconvolution produced smooth, high signal-to-noise scattering distributions for graphene layer detection.
Achieved depth localization precision of 0.1 nm for dopants and 0.2 nm for graphene.

Conclusions:

The developed deconvolution algorithms significantly improve depth resolution in 3D STEM-ADF imaging.
These methods are highly effective for precise 3D localization of heavy dopants and thin material layers.
The deconvolution techniques offer valuable optical sectioning capabilities for 3D STEM-ADF analysis.