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
Link To Document :
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