Large scale fusion of brain imaging modalities and features using Markov-style dynamics in a feature meta-space

Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun

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

Abstract

Brain imaging technology provides a way to sample various aspects of the brain albeit incompletely, providing a rich set of features crossing rest and task conditions, and an ever-growing number of imaging modalities. The conditions being studied with brain imaging data are often extremely complex and it is becoming more common for researchers to employ more than one imaging or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features, modalities or tasks. We propose an intuitive framework based on Markov-style flows for understanding information exchange between features in what we are calling a feature meta-space: that is, a space consisting of an arbitrary number of individual feature spaces, where the features can have any dimension and can be drawn from any data source or modality. We present preliminary work demonstrating the ability of this new framework to identify relationships between disparate features of varying dimensionality.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7716-7719
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period8/25/158/29/15

ASJC Scopus subject areas

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

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  • Cite this

    Miller, R. L., Vergara, V. M., & Calhoun, V. D. (2015). Large scale fusion of brain imaging modalities and features using Markov-style dynamics in a feature meta-space. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 (pp. 7716-7719). [7320180] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7320180