• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Liu, Jinduo (Liu, Jinduo.) | Ji, Junzhong (Ji, Junzhong.) (学者:冀俊忠) | Zhang, Aidong (Zhang, Aidong.) | Liang, Peipeng (Liang, Peipeng.)

收录:

CPCI-S

摘要:

Identifying brain effective connectivity networks from functional magnetic resonance imaging (fMRI) data is an important advanced subject in neuroinformatics in recent years, where the learning method based on bayesian networks (BN) has become a new hot topic in the field. This paper proposes a new method to learn the brain effective connectivity network structure by combining ant colony optimization (ACO) with BN method, named as ACOEC. In the proposed algorithm, a brain effective connectivity network is first mapped onto an ant, and then the ant colony optimization by simulating real ants looking for food is employed to construct network structures and finally an ant with the highest score is obtained as the optimal solution. The experimental results on simulated and real fMRI data sets show that the new method can not only accurately identify the connections and directions of the brain networks, but also quantitatively describe the connection strength of the brain networks, which has a good clinical application prospects.

关键词:

Ant colony optimization Bayesian network Brain effective connectivity network Connection strength fMRI

作者机构:

  • [ 1 ] [Liu, Jinduo]Beijing Univ Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Coll Comp Sci & Technol, Beijing, Peoples R China
  • [ 2 ] [Ji, Junzhong]Beijing Univ Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Coll Comp Sci & Technol, Beijing, Peoples R China
  • [ 3 ] [Zhang, Aidong]SUNY Buffalo, Univ Buffalo, Dept Comp Sci & Engn, Buffalo, NY USA
  • [ 4 ] [Liang, Peipeng]Capital Med Univ, Xuanwu Hosp, Dept Radiol, Beijing Key Lab MRI & Brain Informat, Beijing, Peoples R China

通讯作者信息:

  • 冀俊忠

    [Ji, Junzhong]Beijing Univ Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Coll Comp Sci & Technol, Beijing, Peoples R China

查看成果更多字段

相关关键词:

来源 :

2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)

ISSN: 2156-1125

年份: 2016

页码: 360-367

语种: 英文

被引次数:

WoS核心集被引频次: 7

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 2

在线人数/总访问数:108/3601096
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司