Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity

Barnaly Rashid, Mohammad Reza Arbabshirani, Eswar Damaraju, Robyn Millar, Mustafa S. Cetin, Godfrey D. Pearlson, Vince D. Calhoun

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

4 Scopus citations

Abstract

Recently, there is a growing interest in designing objective prognostic/diagnostic tools based on neuroimaging and other data that display high accuracy and robustness. Small training subjects and very large amount of high dimensional data make it a challenging task to design robust and accurate classifiers for heterogeneous disorders such as schizophrenia. Majority of previous works have focused on classification of schizophrenia from healthy controls while automatic differential diagnosis of schizophrenia from bipolar disorder has been rarely investigated. In this work, we propose a framework for automatic classification of schizophrenia, bipolar and healthy control subjects based on static and dynamic functional network connectivity (FNC) features. Our results show that disrupted functional integration in schizophrenia and bipolar patients as captured by FNC analysis reveal powerful information for automatic discriminative analysis.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Pages251-254
Number of pages4
ISBN (Electronic)9781479923748
DOIs
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2015-July
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States
CityBrooklyn
Period4/16/154/19/15

Keywords

  • bipolar
  • classification
  • dynamic functional network connectivity
  • fMRI
  • schizophrenia

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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