N. Greenberg, Z. Popović, G. Saracino, R. Grimm, J.D. Thomas
{"title":"Novel time-varying 3D display of wall motion, strain, strain rate and torsion for LV function assessment","authors":"N. Greenberg, Z. Popović, G. Saracino, R. Grimm, J.D. Thomas","doi":"10.1109/CIC.2008.4748967","DOIUrl":null,"url":null,"abstract":"Advanced post processing of the standard acquisitions of echocardiographic data (i.e. 3 parallel short-axis views and 3 rotational long axis views) results in a total of 72 time-varying traces of segmental linear strains and 18 traces of segmental rotational data. If one separates the signal into endo, mid, and epicardial myocardial layers, a staggering 246 time-varying traces are available. The synthesis of this amount of data is extremely difficult. Our goal was to develop tools that can visualize this complex dataset in a single representation and use these tools to assess LV function in subjects to examine characteristic patterns.","PeriodicalId":194782,"journal":{"name":"2008 Computers in Cardiology","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Computers in Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2008.4748967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Advanced post processing of the standard acquisitions of echocardiographic data (i.e. 3 parallel short-axis views and 3 rotational long axis views) results in a total of 72 time-varying traces of segmental linear strains and 18 traces of segmental rotational data. If one separates the signal into endo, mid, and epicardial myocardial layers, a staggering 246 time-varying traces are available. The synthesis of this amount of data is extremely difficult. Our goal was to develop tools that can visualize this complex dataset in a single representation and use these tools to assess LV function in subjects to examine characteristic patterns.