Analysis of fMRI Data Using Classical and Bayesian Approaches: A Comparative Study

Abstract

Detection of active areas in a human brain by functional magnetic resonance imaging (fMRI) is a challenging problem in medical imaging. Moreover, determining the onset and end of activation signals can determine temporal relationships required for brain mapping. In this paper, a comparative study for detecting active areas in fMRI data using Bayesian and classical approaches was introduced. It has been found that using Bayesian model provides accurate and sensitive detection.