Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging

Eduardo Castro, Cota Navin Gupta, Manel Martinez-Ramon, Vince Daniel Calhoun, Mohammad R. Arbabshirani, Jessica Turner

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

Abstract

Despite its reliable diagnosis, schizophrenia lacks an objective diagnostic test or a validated biomarker, which prevents a better understanding of this disorder. Structural magnetic resonance imaging (sMRI) has been vastly explored to find consistent abnormality patterns of gray matter concentration (GMC) in schizophrenia, yet we are far from having reached conclusive evidence. This paper presents a machine learning approach based on resampling techniques to find brain regions with consistent patterns of GMC differences between healthy controls and schizophrenia patients, these regions being detected by means of source-based morphometry. This work uses multi-site data from the Mind Clinical Imaging Consortium, which is composed of sMRI data from 124 controls and 110 patients. Our method achieves a better classification rate than other algorithms and detects regions with GMC differences between both groups that are consistent with several findings on the literature. In addition, the results obtained on data from multiple sites suggest that it may be possible to replicate these results on other datasets.

Original languageEnglish (US)
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1513-1516
Number of pages4
ISBN (Print)9781424479290
DOIs
Publication statusPublished - Nov 2 2014
Externally publishedYes
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period8/26/148/30/14

    Fingerprint

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering

Cite this

Castro, E., Gupta, C. N., Martinez-Ramon, M., Calhoun, V. D., Arbabshirani, M. R., & Turner, J. (2014). Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 1513-1516). [6943889] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6943889