Canadian Journal of Statistics

A bayesian signal detection procedure for scale‐space random fields

Journal Article

Abstract

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.

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