DocumentCode
1789448
Title
Brain tissues anisotropic conductivity model based on diffusion tensor imaging
Author
Zhanxiong, W.U. ; Xun, L.I.
Author_Institution
Sch. of Electron. Inf., Hangzhou Dianzi Univ., Hangzhou, China
fYear
2014
fDate
14-16 Oct. 2014
Firstpage
29
Lastpage
31
Abstract
The brain tissue conductivity not only plays key role in the analysis of electroencephalography (EEG) and magnetoencephalography (MEG), but also is one key factor of diagnosing brain functional change in time. Diffusion tensor imaging (DTI) is a non-invasive imaging method, with high spatial-resolution. The importance of conductivity imaging of brain inner tissue is remarkable. This paper summarized the existing WM anisotropic conductivity models, including the model of linear-eigenvalues, the model of electric viscous force balance, Wang-constraint model, volume-constraint model, volume fraction model, and electrochemical model. At last the properties of these models were discussed, and the forward trend of this topic was discussed.
Keywords
biodiffusion; biological tissues; biomedical MRI; brain; eigenvalues and eigenfunctions; electrical conductivity; electrochemistry; electroencephalography; magnetoencephalography; EEG; MEG; WM anisotropic conductivity models; Wang-constraint model; brain functional change diagnosis; brain inner tissue; brain tissue anisotropic conductivity model; diffusion tensor imaging; electric viscous force balance; electrochemical model; electroencephalography; linear-eigenvalue model; magnetoencephalography; noninvasive imaging method; spatial-resolution; volume fraction model; volume-constraint model; Biomedical engineering; Informatics; DTI; WM; conductivity model;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4799-5837-5
Type
conf
DOI
10.1109/BMEI.2014.7002736
Filename
7002736
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