Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia

Jing Sui, Hao He, Jingyu Liu, Qingbao Yu, Tulay Adali, Godfrey D. Pearlson, Vince Daniel Calhoun

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

Abstract

Multi-modal fusion is an effective approach in biomedical imaging which combines multiple data types in a joint analysis and overcomes the problem that each modality provides a limited view of the brain. In this paper, we propose an exploratory fusion model, we term mCCA+jICA, by combining two multivariate approaches: multi-set canonical correlation analysis (mCCA) and joint independent component analysis (jICA). This model can freely combine multiple, disparate data sets and explore their joint information in an accurate and effective manner, so that high decomposition accuracy and valid modal links can be achieved simultaneously. We compared mCCA+jICA with its alternatives in simulation and applied it to real fMRI-DTI-methylation data fusion, to identify brain abnormalities in schizophrenia. The results replicate previous reports and add to our understanding of the neural correlates of schizophrenia, and suggest more generally a promising approach to identify potential brain illness biomarkers.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages2692-2695
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

Fingerprint

Methylation
Independent component analysis
Data fusion
Brain
Schizophrenia
Joints
Biomarkers
Decomposition
Imaging techniques
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Sui, J., He, H., Liu, J., Yu, Q., Adali, T., Pearlson, G. D., & Calhoun, V. D. (2012). Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 2692-2695). [6346519] https://doi.org/10.1109/EMBC.2012.6346519

Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. / Sui, Jing; He, Hao; Liu, Jingyu; Yu, Qingbao; Adali, Tulay; Pearlson, Godfrey D.; Calhoun, Vince Daniel.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2012. p. 2692-2695 6346519.

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

Sui, J, He, H, Liu, J, Yu, Q, Adali, T, Pearlson, GD & Calhoun, VD 2012, Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS., 6346519, pp. 2692-2695, 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012, San Diego, CA, United States, 8/28/12. https://doi.org/10.1109/EMBC.2012.6346519
Sui J, He H, Liu J, Yu Q, Adali T, Pearlson GD et al. Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2012. p. 2692-2695. 6346519 https://doi.org/10.1109/EMBC.2012.6346519
Sui, Jing ; He, Hao ; Liu, Jingyu ; Yu, Qingbao ; Adali, Tulay ; Pearlson, Godfrey D. ; Calhoun, Vince Daniel. / Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2012. pp. 2692-2695
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