Analyzing grey matter diffusivity of autism in the context of white matter connectivity

Hai Li, Zhong Xue, Timothy M. Ellmore, Richard E. Frye, Stephen T. Wong

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

1 Scopus citations

Abstract

Studies have revealed volumetric and connectivity abnormalities in brains of children with autism spectrum disorders (ASD). However, due to the complexity of ASD findings from these studies have been inconsistent. A possible way to improve the robustness of neuroimaging quantification is to introduce biological regularization. Motivated by previous studies on gray matter (GM) diffusivity, which can be used as surrogate biomarker for cortical volume deficits, we proposed a new network-regularized GM diffusivity analysis method to detect the GM diffusivity in the context of white matter (WM) connectivity. Our rationale is that GM diffusivity of anatomically connected regions has similar contributions to group differences. Experiments on simulated and clinical datasets showed better performance of the proposed method both on identification of atypical GM regions and classification of ASD and controls, compared with other methods without network regularization.

Original languageEnglish (US)
Title of host publicationISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro
Pages1150-1153
Number of pages4
DOIs
StatePublished - 2013
Event2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States
Duration: Apr 7 2013Apr 11 2013

Publication series

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

Other

Other2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
CountryUnited States
CitySan Francisco, CA
Period4/7/134/11/13

Keywords

  • Autism
  • brain connectivity
  • DTI
  • SVM

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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