DOU Weibei
|
- Professor
- Name (Simplified Chinese):DOU Weibei
- Name (Simplified Chinese):DOU Weibei
- Name (English):DOU Weibei
- Name (English):DOU Weibei
- School/Department:Department of Electronic Engineering, Tsinghua University
- School/Department:Department of Electronic Engineering, Tsinghua University
- Business Address:Room 4-102,Rohm Building,Tsinghua University, Beijing
- Business Address:Room 4-102,Rohm Building,Tsinghua University, Beijing
- Contact Information:douwb@tsinghua.edu.cn; Tel:010-62781703
- Contact Information:douwb@tsinghua.edu.cn; Tel:010-62781703
- Degree:Doctoral degree
- Degree:Doctoral degree
- Professional Title:Professor
- Professional Title:Professor
- Academic Titles:Professor
- Academic Titles:Professor
- Alma Mater:Université de CAEN, France.
- Alma Mater:Université de CAEN, France.
- Teacher College:DZGCX
- Teacher College:DZGCX
Contact Information
- ZipCode：
- Fax：
- PostalAddress：
- OfficePhone：
- Email：
- Selected Publications
A framework for mapping scalable human brain anatomical networks via diffusion MRI
Release time:2021-12-25 Hits:
- Impact Factor:2.64
- Impact Factor:2.64
- Journal:IEEE-EMBS International Conference on Biomedical & Health Informatics
- Journal:IEEE-EMBS International Conference on Biomedical & Health Informatics
- Abstract:Anatomical network analysis is considered as a significant way to study brains. The attributes of anatomical networks vary across network nodal scales and therefore a scalable network mapping method is needed. Here, a new framework for mapping scalable brain anatomical networks via d-MRI is presented. The modelling of nodes is based on the structural basis of brain connections (white matter) and the scale of network nodes is determined by the clustering number of white matter fibers’ endpoints. d-MRI datasets from glioma patients and healthy people were tested in this framework. All mapped networks have small-world characteristics, and demonstrate the effects of glioma on brain network connectivity
- Abstract:Anatomical network analysis is considered as a significant way to study brains. The attributes of anatomical networks vary across network nodal scales and therefore a scalable network mapping method is needed. Here, a new framework for mapping scalable brain anatomical networks via d-MRI is presented. The modelling of nodes is based on the structural basis of brain connections (white matter) and the scale of network nodes is determined by the clustering number of white matter fibers’ endpoints. d-MRI datasets from glioma patients and healthy people were tested in this framework. All mapped networks have small-world characteristics, and demonstrate the effects of glioma on brain network connectivity
- Co-author:Weibei Dou, Mingyu Zhang, Hongyan Chen, Shaowu Li,Weibei Dou
- Co-author:Weibei Dou, Mingyu Zhang, Hongyan Chen, Shaowu Li,Weibei Dou
- First Author:Ruizhi Liao, Mingyu Zhang, Hongyan Chen, Shaowu Li,Xiao Feng
- First Author:Ruizhi Liao, Mingyu Zhang, Hongyan Chen, Shaowu Li,Xiao Feng
- Indexed by:会议论文
- Indexed by:会议论文
- Correspondence Author:Weibei Dou
- Correspondence Author:Weibei Dou
- Translation or Not:no
- Translation or Not:no
- Date of Publication:2016-02-24
- Date of Publication:2016-02-24