Catarina Runa Miranda, Filipe Soares, I. Sousa, F. Janela, M. Secca
{"title":"Multifractal analysis of blood oxygen level dependent functional magnetic resonance imaging","authors":"Catarina Runa Miranda, Filipe Soares, I. Sousa, F. Janela, M. Secca","doi":"10.1109/ISSPIT.2011.6151572","DOIUrl":null,"url":null,"abstract":"The aim of this work is to propose a multifractal analysis method for Multifractal Detrended Fluctuation analysis (MF-DFA) of Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI). The fMRI signals exhibit a 1/f power spectrum, hence their structure has self-similarity and long memory, being usually successfully analyzed by different fractal analysis methods without a previous knowledge of haemodynamic models. Therefore, to validate activation detection using the MF-DFA method, a comparison study between images obtained using General Linear Model (GLM) and Independent Component Analysis (ICA) was conducted and evaluated by discrimination power, applying Receiver Operating Characteristic (ROC) analysis to the results.","PeriodicalId":288042,"journal":{"name":"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2011.6151572","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
The aim of this work is to propose a multifractal analysis method for Multifractal Detrended Fluctuation analysis (MF-DFA) of Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI). The fMRI signals exhibit a 1/f power spectrum, hence their structure has self-similarity and long memory, being usually successfully analyzed by different fractal analysis methods without a previous knowledge of haemodynamic models. Therefore, to validate activation detection using the MF-DFA method, a comparison study between images obtained using General Linear Model (GLM) and Independent Component Analysis (ICA) was conducted and evaluated by discrimination power, applying Receiver Operating Characteristic (ROC) analysis to the results.