A new method to extract the conductivity tensor of brain inner tissues

Zhanxiong Wu; Shanan Zhu; Bin He

doi:10.1109/BMEI.2010.5639249

A new method to extract the conductivity tensor of brain inner tissues

Zhanxiong Wu, Shanan Zhu, Bin He

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The conductivity of brain inner tisssue is the key factor in EEG/MEG research. The brain tissue is inhomogeneous, and specially white matter exhibits serious anisotropic conductivity. The traditional methods such as electrical impedance tomography(EIT) is hard to solve the anisotropic conductivity problem. This paper put forward a new method to covert diffusion tensor to conductivity tensor based on diffusion tensor imaging (DTI) technology. This method incorporates the parameter of ions'concentration based on Stokes-Einstein and Nernst-Einstein equations. At last the method was testified on a human subject DTI dataset. The accuracy of this method is mainly determined by the parameter of diffusion-weighted time.

Original language	English (US)
Title of host publication	Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
Pages	1300-1302
Number of pages	3
DOIs	https://doi.org/10.1109/BMEI.2010.5639249
State	Published - 2010
Event	3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010 - Yantai, China Duration: Oct 16 2010 → Oct 18 2010

Publication series

Name	Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010
Volume	3

Other

Other	3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010
Country/Territory	China
City	Yantai
Period	10/16/10 → 10/18/10

Keywords

DTI
EEG/MEG
EIT

Access

10.1109/BMEI.2010.5639249

OpenUrl availability

Full text

Cite this

Wu, Z., Zhu, S., & He, B. (2010). A new method to extract the conductivity tensor of brain inner tissues. In Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010 (pp. 1300-1302). Article 5639249 (Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010; Vol. 3). https://doi.org/10.1109/BMEI.2010.5639249

A new method to extract the conductivity tensor of brain inner tissues. / Wu, Zhanxiong; Zhu, Shanan; He, Bin.
Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010. 2010. p. 1300-1302 5639249 (Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wu, Z, Zhu, S & He, B 2010, A new method to extract the conductivity tensor of brain inner tissues. in Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010., 5639249, Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010, vol. 3, pp. 1300-1302, 3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010, Yantai, China, 10/16/10. https://doi.org/10.1109/BMEI.2010.5639249

@inproceedings{339d2b4eaa70464c8a725091515dc3ab,

title = "A new method to extract the conductivity tensor of brain inner tissues",

abstract = "The conductivity of brain inner tisssue is the key factor in EEG/MEG research. The brain tissue is inhomogeneous, and specially white matter exhibits serious anisotropic conductivity. The traditional methods such as electrical impedance tomography(EIT) is hard to solve the anisotropic conductivity problem. This paper put forward a new method to covert diffusion tensor to conductivity tensor based on diffusion tensor imaging (DTI) technology. This method incorporates the parameter of ions'concentration based on Stokes-Einstein and Nernst-Einstein equations. At last the method was testified on a human subject DTI dataset. The accuracy of this method is mainly determined by the parameter of diffusion-weighted time.",

keywords = "DTI, EEG/MEG, EIT",

author = "Zhanxiong Wu and Shanan Zhu and Bin He",

year = "2010",

doi = "10.1109/BMEI.2010.5639249",

language = "English (US)",

isbn = "9781424464968",

series = "Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010",

pages = "1300--1302",

booktitle = "Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010",

note = "3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010 ; Conference date: 16-10-2010 Through 18-10-2010",

}

TY - GEN

T1 - A new method to extract the conductivity tensor of brain inner tissues

AU - Wu, Zhanxiong

AU - Zhu, Shanan

AU - He, Bin

PY - 2010

Y1 - 2010

N2 - The conductivity of brain inner tisssue is the key factor in EEG/MEG research. The brain tissue is inhomogeneous, and specially white matter exhibits serious anisotropic conductivity. The traditional methods such as electrical impedance tomography(EIT) is hard to solve the anisotropic conductivity problem. This paper put forward a new method to covert diffusion tensor to conductivity tensor based on diffusion tensor imaging (DTI) technology. This method incorporates the parameter of ions'concentration based on Stokes-Einstein and Nernst-Einstein equations. At last the method was testified on a human subject DTI dataset. The accuracy of this method is mainly determined by the parameter of diffusion-weighted time.

AB - The conductivity of brain inner tisssue is the key factor in EEG/MEG research. The brain tissue is inhomogeneous, and specially white matter exhibits serious anisotropic conductivity. The traditional methods such as electrical impedance tomography(EIT) is hard to solve the anisotropic conductivity problem. This paper put forward a new method to covert diffusion tensor to conductivity tensor based on diffusion tensor imaging (DTI) technology. This method incorporates the parameter of ions'concentration based on Stokes-Einstein and Nernst-Einstein equations. At last the method was testified on a human subject DTI dataset. The accuracy of this method is mainly determined by the parameter of diffusion-weighted time.

KW - DTI

KW - EEG/MEG

KW - EIT

UR - http://www.scopus.com/inward/record.url?scp=78650664082&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650664082&partnerID=8YFLogxK

U2 - 10.1109/BMEI.2010.5639249

DO - 10.1109/BMEI.2010.5639249

M3 - Conference contribution

AN - SCOPUS:78650664082

SN - 9781424464968

T3 - Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010

SP - 1300

EP - 1302

BT - Proceedings - 2010 3rd International Conference on Biomedical Engineering and Informatics, BMEI 2010

T2 - 3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010

Y2 - 16 October 2010 through 18 October 2010

ER -

A new method to extract the conductivity tensor of brain inner tissues

Abstract

Publication series

Other

Keywords

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this