Monte-Carlo based neuroimaging set-level multiple-comparison correction

Kewei Chen, Eric M. Reiman, Daniel Bandy, Gene E. Alexander

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

In neuroimaging studies, the type 1 error attributable to the number of independent regional comparisons should be considered. Implemented algorithms approximate the type 1 errors assuming Gaussian or Gaussian-based distribution, are typically for a contiguous/convex volume, and are for conventional hypothesis related to at least one or more clusters of certain size/height. As a complement, a Monte-Carlo algorithm is proposed to calculate the type 1 error of various types of hypotheses a researcher might have, and is applicable to Gaussian and non-Gaussian distributions over non-contiguous, non-convex and convoluted search volume.

Original languageEnglish (US)
Pages (from-to)11-15
Number of pages5
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume36
Issue number15
DOIs
StatePublished - Jan 1 2003
Event5th IFAC Symposium on Modelling and Control in Biomedical Systems 2003 - Melbourne, Australia
Duration: Aug 21 2003Aug 23 2003

Keywords

  • Image analysis
  • Image processing
  • Magnetic resonance imaging
  • Monte-carlo simulation
  • Positron emission tomography
  • Statistical inference

ASJC Scopus subject areas

  • Control and Systems Engineering

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