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Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments

In situ scanning transmission electron microscopy is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically, the process of identi...

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Autores principales: Moeglein, W. A., Griswold, R., Mehdi, B. L., Browning, N. D., Teuton, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313570/
https://www.ncbi.nlm.nih.gov/pubmed/28261540
http://dx.doi.org/10.1186/s40679-016-0034-x
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author Moeglein, W. A.
Griswold, R.
Mehdi, B. L.
Browning, N. D.
Teuton, J.
author_facet Moeglein, W. A.
Griswold, R.
Mehdi, B. L.
Browning, N. D.
Teuton, J.
author_sort Moeglein, W. A.
collection PubMed
description In situ scanning transmission electron microscopy is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically, the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage, etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here, we show that video shot boundary detection can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40679-016-0034-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-53135702017-03-01 Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments Moeglein, W. A. Griswold, R. Mehdi, B. L. Browning, N. D. Teuton, J. Adv Struct Chem Imaging Methodology In situ scanning transmission electron microscopy is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically, the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage, etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here, we show that video shot boundary detection can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40679-016-0034-x) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-01-03 2017 /pmc/articles/PMC5313570/ /pubmed/28261540 http://dx.doi.org/10.1186/s40679-016-0034-x Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Methodology
Moeglein, W. A.
Griswold, R.
Mehdi, B. L.
Browning, N. D.
Teuton, J.
Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title_full Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title_fullStr Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title_full_unstemmed Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title_short Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
title_sort applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313570/
https://www.ncbi.nlm.nih.gov/pubmed/28261540
http://dx.doi.org/10.1186/s40679-016-0034-x
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