Cluster Analysis Revisited
FMRIB Technical Report TR00DF1
David E. Flitney and Mark Jenkinson
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB),
Department of Clinical Neurology, University of Oxford, John Radcliffe Hospital,
Headley Way, Headington, Oxford, UK
To complete the analysis of any FMRI experiment it is necessary to
compensate for the multiple comparisons problem inherent in making a
large number of simultaneous statistical tests. One method for
accomplishing this is to employ cluster analysis to bolster one's
confidence in any particular statistical result. The following
review combines the well known works in this field to form the basis
of an implementation of the Gaussian random field theory applied to
the analysis of FMRI statistic images.
keywords: FMRI, Gaussian Random Fields, smoothness estimation,
multiple comparisons, statistical significance.