Scalable Brain Network Construction on White Matter Fibers

被引：11

作者：

Chung, Moo K. ^{[1
]}

Adluru, Nagesh ^{[1
]}

Dalton, Kim M. ^{[1
]}

Alexander, Andrew L. ^{[1
]}

Davidson, Richard J. ^{[1
]}

机构：

[1] Univ Wisconsin, Dept Biostat & Med Informat, Madison, WI USA

来源：

MEDICAL IMAGING 2011: IMAGE PROCESSING | 2011年 / 7962卷

关键词：

D O I：

10.1117/12.874245

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

DTI offers a unique opportunity to characterize the structural connectivity of the human brain non-invasively by tracing white matter fiber tracts. Whole brain tractography studies routinely generate up to half million tracts per brain, which serves as edges in an extremely large 3D graph with up to half million edges. Currently there is no agreed-upon method for constructing the brain structural network graphs out of large number of white matter tracts. In this paper, we present a scalable iterative framework called the epsilon-neighbor method for building a network graph and apply it to testing abnormal connectivity in autism.

引用

页数：6

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