{"title":"A method for comparing time series by untangling time-dependent and independent variations in biological processes","authors":"A. J. Thottupattu, J. Sivaswamy","doi":"10.1145/3681795","DOIUrl":null,"url":null,"abstract":"Biological processes like growth, aging, and disease progression are generally studied with follow-up scans taken at different time points, i.e., image time series (TS) based analysis. Image time series represents the evolution of anatomy over time, but different anatomies may have different structural characteristics and temporal paths. Therefore, separating the time-dependent path difference and time-independent basic anatomy/shape changes is important when comparing two image time series to understand the causes of the observed differences better. A method to untangle and quantify the path and shape difference between the TS is presented in this paper. The proposed method is evaluated with simulated and adult and fetal neuro templates. Results show that the metric can separate and quantify the path and shape differences between TS.","PeriodicalId":72043,"journal":{"name":"ACM transactions on computing for healthcare","volume":"45 20","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM transactions on computing for healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3681795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Biological processes like growth, aging, and disease progression are generally studied with follow-up scans taken at different time points, i.e., image time series (TS) based analysis. Image time series represents the evolution of anatomy over time, but different anatomies may have different structural characteristics and temporal paths. Therefore, separating the time-dependent path difference and time-independent basic anatomy/shape changes is important when comparing two image time series to understand the causes of the observed differences better. A method to untangle and quantify the path and shape difference between the TS is presented in this paper. The proposed method is evaluated with simulated and adult and fetal neuro templates. Results show that the metric can separate and quantify the path and shape differences between TS.