K. Rafik, B.H. Ahmed, F. Imed, Taleb-Ahmed Abdelmalik
{"title":"Recursive sLORETA-FOCUSS Algorithm for EEG Dipoles Localization","authors":"K. Rafik, B.H. Ahmed, F. Imed, Taleb-Ahmed Abdelmalik","doi":"10.1109/IPTA.2008.4743745","DOIUrl":null,"url":null,"abstract":"The electrical activity inside the brain consists of currents generated by biochemical sources at cellular level. This activity can be measured by an electroencephalography. Neurologists have been interested in determining the location of the epileptogenic zones from measured potential on the scalp in order to avoid invasive techniques. The problem is recognizing by inverse problem. In this paper we propose an amelioration of the inverse problem method \"sLORETA-FOCUSS\" given by smoothing the current density distribution. We present a comparative study of the sLORETA-FOCUSS and the new solution named recursive sLORETA-FOCUSS. The found results demonstrate that the new method is able to give good results in term of localization error, simulated time, and precision of reconstruction in 3D.","PeriodicalId":384072,"journal":{"name":"2008 First Workshops on Image Processing Theory, Tools and Applications","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First Workshops on Image Processing Theory, Tools and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2008.4743745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The electrical activity inside the brain consists of currents generated by biochemical sources at cellular level. This activity can be measured by an electroencephalography. Neurologists have been interested in determining the location of the epileptogenic zones from measured potential on the scalp in order to avoid invasive techniques. The problem is recognizing by inverse problem. In this paper we propose an amelioration of the inverse problem method "sLORETA-FOCUSS" given by smoothing the current density distribution. We present a comparative study of the sLORETA-FOCUSS and the new solution named recursive sLORETA-FOCUSS. The found results demonstrate that the new method is able to give good results in term of localization error, simulated time, and precision of reconstruction in 3D.