Literature DB >> 34101814

Improved efficiency in automated acquisition of ultra-high-resolution electron holograms using automated target detection.

Fumiaki Ichihashi1, Toshiaki Tanigaki1, Tetsuya Akashi1, Yoshio Takahashi1, Kohei Kusada2, Takehiro Tamaoka3, Hiroshi Kitagawa2, Hiroyuki Shinada1, Yasukazu Murakami3,4.   

Abstract

An automated hologram acquisition system for big-data analysis and for improving the statistical precision of phase analysis has been upgraded with automated particle detection technology. The coordinates of objects in low-magnification images are automatically detected using zero-mean normalized cross-correlation with preselected reference images. In contrast with the conventional scanning acquisitions from the whole area of a microgrid and/or a thin specimen, the new method allows efficient data collections only from the desired fields of view including the particles. The acquisition time of the cubic/triangular nanoparticles that were observed was shortened by about one-fifty eighth that of the conventional scanning acquisition method because of efficient data collections. The developed technology can improve statistical precision in electron holography with shorter acquisition time and is applicable to the analysis of electromagnetic fields for various kinds of nanoparticles.
© The Author(s) 2021. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  big-data; electron holography; image analysis; particle detection

Year:  2021        PMID: 34101814     DOI: 10.1093/jmicro/dfab021

Source DB:  PubMed          Journal:  Microscopy (Oxf)        ISSN: 2050-5698            Impact factor:   1.571


  1 in total

1.  Detection of Pine Wilt Nematode from Drone Images Using UAV.

Authors:  Zhengzhi Sun; Mayire Ibrayim; Askar Hamdulla
Journal:  Sensors (Basel)       Date:  2022-06-22       Impact factor: 3.847

  1 in total

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