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Title: Image registration of low signal-to-noise cryo-STEM data

Abstract

Combining multiple fast image acquisitions to mitigate scan noise and drift artifacts has proven essential for picometer precision, quantitative analysis of atomic resolution scanning transmission electron microscopy (STEM) data. For very low signal-to-noise ratio (SNR) image stacks – frequently required for undistorted imaging at liq- uid nitrogen temperatures – image registration is particularly delicate, and standard approaches may either fail, or produce subtly specious reconstructed lattice images. We present an approach which effectively registers and averages image stacks which are challenging due to their low-SNR and propensity for unit cell misalignments. Registering all possible image pairs in a multi-image stack leads to significant information surplus. In combination with a simple physical picture of stage drift, this enables identi cation of incorrect image registrations, and determination of the optimal image shifts from the complete set of relative shifts. Here, we demonstrate the effectiveness of our approach on experimental, cryogenic STEM datasets, highlighting subtle artifacts endemic to low-SNR lattice images and how they can be avoided. High-SNR average images with information transfer out to 0.72 Å are achieved at 300 kV and with the sample cooled to near liquid nitrogen temperature.

Authors:
 [1];  [1];  [1];  [1]; ORCiD logo [1];  [1];  [2]; ORCiD logo [2];  [1];  [1];  [3];  [4];  [4];  [4];  [5];  [1];  [2];  [6];  [1]
  1. Cornell Univ., Ithaca, NY (United States)
  2. The Johns Hopkins Univ., Baltimore, MD (United States)
  3. Argonne National Lab. (ANL), Argonne, IL (United States); Harvard Univ., Cambridge, MA (United States)
  4. Rutgers Univ., Piscataway, NJ (United States)
  5. Argonne National Lab. (ANL), Argonne, IL (United States)
  6. Cornell Univ., Ithaca, NY (United States); Univ. of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
Gordon and Betty Moore Foundation; Air Force Research Laboratory (AFRL), Air Force Office of Scientific Research (AFOSR); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division; National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1479486
Alternate Identifier(s):
OSTI ID: 1703388
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Ultramicroscopy
Additional Journal Information:
Journal Volume: 191; Journal Issue: C; Journal ID: ISSN 0304-3991
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; Atomic Resolution; Cryogenic STEM (cryo-STEM); Image reconstruction; Low signal-to-noise ratio (SNR); Rigid registration; Scanning Transmission Electron Microscopy (STEM)

Citation Formats

Savitzky, Benjamin H., El Baggari, Ismail, Clement, Colin B., Waite, Emily, Goodge, Berit H., Baek, David J., Sheckelton, John P., Pasco, Christopher, Nair, Hari, Schreiber, Nathaniel J., Hoffman, Jason, Admasu, Alemayehu S., Kim, Jaewook, Cheong, Sang -Wook, Bhattacharya, Anand, Schlom, Darrell G., McQueen, Tyrel M., Hovden, Robert, and Kourkoutis, Lena F. Image registration of low signal-to-noise cryo-STEM data. United States: N. p., 2018. Web. doi:10.1016/j.ultramic.2018.04.008.
Savitzky, Benjamin H., El Baggari, Ismail, Clement, Colin B., Waite, Emily, Goodge, Berit H., Baek, David J., Sheckelton, John P., Pasco, Christopher, Nair, Hari, Schreiber, Nathaniel J., Hoffman, Jason, Admasu, Alemayehu S., Kim, Jaewook, Cheong, Sang -Wook, Bhattacharya, Anand, Schlom, Darrell G., McQueen, Tyrel M., Hovden, Robert, & Kourkoutis, Lena F. Image registration of low signal-to-noise cryo-STEM data. United States. https://doi.org/10.1016/j.ultramic.2018.04.008
Savitzky, Benjamin H., El Baggari, Ismail, Clement, Colin B., Waite, Emily, Goodge, Berit H., Baek, David J., Sheckelton, John P., Pasco, Christopher, Nair, Hari, Schreiber, Nathaniel J., Hoffman, Jason, Admasu, Alemayehu S., Kim, Jaewook, Cheong, Sang -Wook, Bhattacharya, Anand, Schlom, Darrell G., McQueen, Tyrel M., Hovden, Robert, and Kourkoutis, Lena F. Fri . "Image registration of low signal-to-noise cryo-STEM data". United States. https://doi.org/10.1016/j.ultramic.2018.04.008. https://www.osti.gov/servlets/purl/1479486.
@article{osti_1479486,
title = {Image registration of low signal-to-noise cryo-STEM data},
author = {Savitzky, Benjamin H. and El Baggari, Ismail and Clement, Colin B. and Waite, Emily and Goodge, Berit H. and Baek, David J. and Sheckelton, John P. and Pasco, Christopher and Nair, Hari and Schreiber, Nathaniel J. and Hoffman, Jason and Admasu, Alemayehu S. and Kim, Jaewook and Cheong, Sang -Wook and Bhattacharya, Anand and Schlom, Darrell G. and McQueen, Tyrel M. and Hovden, Robert and Kourkoutis, Lena F.},
abstractNote = {Combining multiple fast image acquisitions to mitigate scan noise and drift artifacts has proven essential for picometer precision, quantitative analysis of atomic resolution scanning transmission electron microscopy (STEM) data. For very low signal-to-noise ratio (SNR) image stacks – frequently required for undistorted imaging at liq- uid nitrogen temperatures – image registration is particularly delicate, and standard approaches may either fail, or produce subtly specious reconstructed lattice images. We present an approach which effectively registers and averages image stacks which are challenging due to their low-SNR and propensity for unit cell misalignments. Registering all possible image pairs in a multi-image stack leads to significant information surplus. In combination with a simple physical picture of stage drift, this enables identi cation of incorrect image registrations, and determination of the optimal image shifts from the complete set of relative shifts. Here, we demonstrate the effectiveness of our approach on experimental, cryogenic STEM datasets, highlighting subtle artifacts endemic to low-SNR lattice images and how they can be avoided. High-SNR average images with information transfer out to 0.72 Å are achieved at 300 kV and with the sample cooled to near liquid nitrogen temperature.},
doi = {10.1016/j.ultramic.2018.04.008},
journal = {Ultramicroscopy},
number = C,
volume = 191,
place = {United States},
year = {2018},
month = {4}
}

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