A Bayesian signal detection procedure for scale-space random fieids

M. Farid Rohani, Khalil Shafie, Siamak Noorbaloochi

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


The authors consider the problem of searching for activation in brain images obtained from functional magnetic resonance imaging and the corresponding functional signal detection problem. They develop a Bayesian procedure to detect signals existing within noisy images when the image is modeled as a scale space random field. Their procedure is based on the Radon-Nikodym derivative, which is used as the Bayes factor for assessing the point null hypothesis of no signal. They apply their method to data from the Montreal Neurological Institute.

Original languageEnglish (US)
Pages (from-to)311-325
Number of pages15
JournalCanadian Journal of Statistics
Issue number2
StatePublished - Jun 2006


  • Bayes factor
  • Scale space random fields
  • Signal detection


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