Integration of network topological features and graph Fourier transform for fMRI data analysis

Junqi Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu Ping Wang

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

1 Scopus citations

Abstract

Motivated by the recent progress in both graph signal processing and brain imaging, we integrate both techniques for complex brain network analysis. In particular, we address the challenge of evaluating the difference of functional connectivity networks between different age groups from resting state functional magnetic resonance imaging (RS-fMRI) observations. We proposed an approach to combine commonly used topological features from complex network analysis with the Graph Fourier Transform (GFT). Since GFT contributes to find the significant subspace of the original signal while topological features reveal the morphological structure of the brain network, they provide complementary information for characterizing brain networks. The method was validated on resting-state fMRI imaging data from Philadelphia Neurodevelopmental Cohort (PNC) dataset, comprised of normally developing adolescents from 8 to 22. The result shows that the model works well in distinguishing different age groups with an accuracy of 86.64% for 389 subjects.

Original languageEnglish (US)
Title of host publication2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PublisherIEEE Computer Society
Pages92-96
Number of pages5
ISBN (Electronic)9781538636367
DOIs
StatePublished - May 23 2018
Event15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States
Duration: Apr 4 2018Apr 7 2018

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2018-April
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
CountryUnited States
CityWashington
Period4/4/184/7/18

Keywords

  • Graph Fourier transform
  • Lasso
  • Network
  • SVM
  • Topological features

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Wang, J., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. P. (2018). Integration of network topological features and graph Fourier transform for fMRI data analysis. In 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018 (pp. 92-96). (Proceedings - International Symposium on Biomedical Imaging; Vol. 2018-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2018.8363530