Justin T. Mulvey , Katen P. Iyer , Tomàs Ortega , Jovany G. Merham , Yevheniy Pivak , Hongyu Sun , Allon I. Hochbaum , Joseph P. Patterson
{"title":"利用结构差异度量将电化学刺激与液体电子显微镜视频中的结构变化联系起来","authors":"Justin T. Mulvey , Katen P. Iyer , Tomàs Ortega , Jovany G. Merham , Yevheniy Pivak , Hongyu Sun , Allon I. Hochbaum , Joseph P. Patterson","doi":"10.1016/j.ultramic.2023.113894","DOIUrl":null,"url":null,"abstract":"<div><p>In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.</p></div>","PeriodicalId":23439,"journal":{"name":"Ultramicroscopy","volume":"257 ","pages":"Article 113894"},"PeriodicalIF":2.1000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304399123002115/pdfft?md5=2378b1bb70879e5ee3b2fafc25142455&pid=1-s2.0-S0304399123002115-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Correlating electrochemical stimulus to structural change in liquid electron microscopy videos using the structural dissimilarity metric\",\"authors\":\"Justin T. Mulvey , Katen P. Iyer , Tomàs Ortega , Jovany G. Merham , Yevheniy Pivak , Hongyu Sun , Allon I. Hochbaum , Joseph P. Patterson\",\"doi\":\"10.1016/j.ultramic.2023.113894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.</p></div>\",\"PeriodicalId\":23439,\"journal\":{\"name\":\"Ultramicroscopy\",\"volume\":\"257 \",\"pages\":\"Article 113894\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0304399123002115/pdfft?md5=2378b1bb70879e5ee3b2fafc25142455&pid=1-s2.0-S0304399123002115-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ultramicroscopy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304399123002115\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROSCOPY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ultramicroscopy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304399123002115","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROSCOPY","Score":null,"Total":0}
Correlating electrochemical stimulus to structural change in liquid electron microscopy videos using the structural dissimilarity metric
In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.
期刊介绍:
Ultramicroscopy is an established journal that provides a forum for the publication of original research papers, invited reviews and rapid communications. The scope of Ultramicroscopy is to describe advances in instrumentation, methods and theory related to all modes of microscopical imaging, diffraction and spectroscopy in the life and physical sciences.