Discriminative brain effective connectivity analysis for alzheimer's disease: A kernel learning approach upon sparse gaussian bayesian network

Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Analyzing brain networks from neuroimages is becoming a promising approach in identifying novel connectivity-based biomarkers for the Alzheimer's disease (AD). In this regard, brain ''effective connectivity' analysis, which studies the causal relationship among brain regions, is highly challenging and of many research opportunities. Most of the existing works in this field use generative methods. Despite their success in data representation and other important merits, generative methods are not necessarily discriminative, which may cause the ignorance of subtle but critical disease-induced changes. In this paper, we propose a learning-based approach that integrates the benefits of generative and discriminative methods to recover effective connectivity. In particular, we employ Fisher kernel to bridge the generative models of sparse Bayesian networks (SBN) and the discriminative classifiers of SVMs, and convert the SBN parameter learning to Fisher kernel learning via minimizing a generalization error bound of SVMs. Our method is able to simultaneously boost the discriminative power of both the generative SBN models and the SBN-induced SVM classifiers via Fisher kernel. The proposed method is tested on analyzing brain effective connectivity for AD from ADNI data, and demonstrates significant improvements over the state-of-the-art work.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Pages2243-2250
Number of pages8
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013 - Portland, OR, United States
Duration: 2013 Jun 232013 Jun 28

Other

Other26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013
CountryUnited States
CityPortland, OR
Period13/6/2313/6/28

Fingerprint

Bayesian networks
Brain
Classifiers
Biomarkers

Keywords

  • Alzheimer's Disease
  • Brain connectivity analysis
  • Discriminative learning
  • sparse Bayesian Network

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Zhou, L., Wang, L., Liu, L., Ogunbona, P., & Shen, D. (2013). Discriminative brain effective connectivity analysis for alzheimer's disease: A kernel learning approach upon sparse gaussian bayesian network. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2243-2250). [6619135] https://doi.org/10.1109/CVPR.2013.291

Discriminative brain effective connectivity analysis for alzheimer's disease : A kernel learning approach upon sparse gaussian bayesian network. / Zhou, Luping; Wang, Lei; Liu, Lingqiao; Ogunbona, Philip; Shen, Dinggang.

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. p. 2243-2250 6619135.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, L, Wang, L, Liu, L, Ogunbona, P & Shen, D 2013, Discriminative brain effective connectivity analysis for alzheimer's disease: A kernel learning approach upon sparse gaussian bayesian network. in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition., 6619135, pp. 2243-2250, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013, Portland, OR, United States, 13/6/23. https://doi.org/10.1109/CVPR.2013.291
Zhou L, Wang L, Liu L, Ogunbona P, Shen D. Discriminative brain effective connectivity analysis for alzheimer's disease: A kernel learning approach upon sparse gaussian bayesian network. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. p. 2243-2250. 6619135 https://doi.org/10.1109/CVPR.2013.291
Zhou, Luping ; Wang, Lei ; Liu, Lingqiao ; Ogunbona, Philip ; Shen, Dinggang. / Discriminative brain effective connectivity analysis for alzheimer's disease : A kernel learning approach upon sparse gaussian bayesian network. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013. pp. 2243-2250
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