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

Content Provider	IEEE Xplore Digital Library
Author	Jing Sui Hao He Jingyu Liu Qingbao Yu Adali, T. Pearlson, G.D. Calhoun, V.D.
Copyright Year	2012
Description	Author affiliation: Mind Res. Network, Albuquerque, NM, USA (Jing Sui; Hao He; Jingyu Liu; Qingbao Yu; Calhoun, V.D.) \|\| Dept. of CSEE, Univ. of Maryland, Baltimore, MD, USA (Adali, T.) \|\| Olin Neuropsychiatry Res. Center, Hartford, CT, USA (Pearlson, G.D.)
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.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	2692
Ending Page	2695
File Size	1598390
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346519
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Joints Correlation Brain modeling Diffusion tensor imaging Genetics Accuracy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Three-Way (N-way) Fusion of Brain Imaging Data Based on mCCA+jICA and Its Application to Discriminating Schizophrenia

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Three-Way (N-way) Fusion of Brain Imaging Data Based on mCCA+jICA and Its Application to Discriminating Schizophrenia

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